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Scale AI is seeking a technically rigorous and driven AI Research Engineer to join our Enterprise Evaluations team. This high-impact role is critical to our mission of delivering the industry's leading GenAI Evaluation Suite. You will be a hands-on contributor to the core systems that ensure the safety, reliability, and continuous improvement of LLM-powered workflows and agents for the enterprise. The ideal candidate has a strong foundational knowledge of large language models, a passion for tackling complex evaluation challenges, and thrives in a dynamic, fast-paced research environment. We are looking for an engineer who can think outside the box, stays current with the latest literature in AI evaluation, and is passionate about integrating novel research ideas into our workflows to build best-in-class evaluation systems. • Partner with Scale's Operations team and enterprise customers to translate ambiguity into structured evaluation data, guiding the creation and maintenance of gold-standard human-rated datasets and expert rubrics that anchor AI evaluation systems., • Analyze feedback and collected data to identify patterns, refine evaluation frameworks, and establish iterative improvement loops that enhance the quality and relevance of human-curated assessments., • Design, research, and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems. This includes creating models that critique, grade, and explain agent outputs (e.g., RLAIF, model-judging-model setups), along with scalable evaluation pipelines and diagnostic tools., • Pursue research initiatives that explore new methodologies for automatically analyzing, evaluating, and improving the behavior of enterprise agents, pushing the boundaries of how AI systems are assessed and optimized in real-world contexts., • Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience., • 2+ years of experience in Machine Learning or Applied Research, focused on applied ML systems or evaluation infrastructure., • Hands-on experience with Large Language Models (LLMs) and Generative AI in professional or research environments., • Strong understanding of frontier model evaluation methodologies and the current research landscape., • Proficiency in Python and major ML frameworks (e.g., PyTorch, TensorFlow)., • Solid engineering and statistical analysis foundation, with experience developing data-driven methods for assessing model quality., • Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field., • Published research in leading ML or AI conferences such as NeurIPS, ICML, ICLR, or KDD., • Experience designing, building, or deploying LLM-as-a-Judge frameworks or other automated evaluation systems for complex models., • Experience collaborating with operations or external teams to define high-quality human annotator guidelines., • Expertise in ML research engineering, stochastic systems, observability, or LLM-powered applications for model evaluation and analysis., • Experience contributing to scalable pipelines that automate the evaluation and monitoring of large-scale models and agents. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Judi Health is an enterprise health technology company providing a comprehensive suite of solutions for employers and health plans, including: • Capital Rx, a public benefit corporation delivering full-service pharmacy benefit management (PBM) solutions to self-insured employers,, • Judi Health, which offers full-service health benefit management solutions to employers, TPAs, and health plans, and Position Summary: Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Senior Machine Learning Engineer. We are looking for an experienced software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services. In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare. Responsibilities: * Design, develop, and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. * Develop and maintain backend services using Python, focusing on AI-driven applications. * Design and implement APIs for seamless integration with AI models and services. * Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning. * Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment. * Participate in code reviews, testing, and quality assurance processes. * Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. * Implement system telemetry, A/B testing and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. * Document and communicate development processes, system designs, and architectural decisions. * Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. * Minimum 6+ years of experience in industry with a strong focus on ML solutions development and production deployment. * Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development. * Strong proficiency in Python and familiarity with ML libraries such as PyTorch. * Statistical Machine Learning and Artificial Intelligence in the context of NLP, Speech, RAG, Virtual Agents, and/or Document Processing technologies * Familiarity with cloud platforms such as AWS or Azure. * Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma etc. Experience developing and fine-tuning prompts on any of the GenAI services * Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. * Passion for customer, innovation, product quality, service excellence, and test engineering * The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment. * Experience working with microservices/an API-based application paradigm. * Good written communication skills that enable collaboration in a remote environment. This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals. Salary Range$180,000—$220,000 USD All employees are responsible for adherence to the Capital Rx Code of Conduct including the reporting of non-compliance. This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals. Judi Health values a diverse workplace and celebrates the diversity that each employee brings to the table. We are proud to provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, medical condition, genetic information, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. By submitting an application, you agree to the retention of your personal data for consideration for a future position at Judi Health. More details about Judi Health's privacy practices can be found at___.

All locations New York, United States; Hartford, United States; San Francisco, United States; Location: Hartford, San Francisco, or New York City Job Description The Insure AI team is part of the New and Green Technologies business unit in Munich Re's Global Specialty Insurance division. You would join an experienced international business unit structuring insurance and reinsurance solutions for risks of AI and Generative AI applications. As a Research Scientist Intern, your focus will be contributing to research on developing statistically robust quantification and assessment methodologies for AI and GenAI models. Please visit our website to find out more about the team: ___. The location of the position is flexible, with options being San Francisco, New York, or Hartford, CT. Your Job * Conduct independent research on statistical and methodological approaches for assessing risks associated with AI and GenAI models. * Drive research projects with creativity and scientific rigor-design experiments, generate hypotheses, and proactively explore new analytical directions. * Develop and test uncertaintyquantification methods, including conformal prediction, calibration techniques, predictive intervals, and other approaches relevant for AI risk assessment. * Support the development of novel frameworks for estimating model risks, detecting performance drift, identifying discrimination and algorithmic harms, and characterizing AI model failure modes. * Contribute to research papers with the team, summarizing key findings and conducting literature reviews for academic publication. * Present research results to both technical and nontechnical stakeholders within Munich Re, as well as at academic conferences. Your Profile * Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Engineering, or a related quantitative field. * Demonstrated ability to independently drive research projects with creativity, curiosity, and scientific rigor. * Strong foundation in statistical modeling, machine learning theory, and experimental design. * Experience with uncertaintyquantification methods such as conformal prediction, model calibration, or related statistical techniques. * Familiarity with AI/GenAI model evaluation including robustness testing, performancedrift detection, fairness and discrimination assessment, and other risk analysis. * Proficiency in Python and commonly used machine learning frameworks (e.g., PyTorch, TensorFlow, NumPy, Scikitlearn). * Ability to synthesize research findings, conduct literature reviews, and contribute to academicstyle writing. * Strong communication skills, with the ability to present complex ideas clearly to both technical and nontechnical audiences. At The Hartford Steam Boiler, a subsidiary of Munich Re, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services. We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. The work environment characteristics, and any physical and mental requirements described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Other duties, responsibilities and activities may change or be assigned at any time with or without notice. The Company is open to considering candidates in numerous locations, including California. The hourly ranged posted below applies to the Company's Hartford, CT location. • The hourly range for this position is $41.00-$49.00., • The hourly estimate displayed represents the typical hourly range of candidates hired. Factors that may be used to determine your actual hourly rate may include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range. ___ Save job

Senior Machine Learning Engineer - Model Evaluations, Public Sector The Public Sector ML team at Scale deploys advanced AI systems-including LLMs, agentic models, and multimodal pipelines-into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions. You will: • Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge-based evaluations., • Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes., • Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing., • Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes., • Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems., • Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases. Ideally you'd have: • Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings., • Strong programming skills in Python; experience with TensorFlow or PyTorch., • Background in algorithms, data structures, and object-oriented programming., • Experience with LLM pipelines, simulation environments, or automated evaluation systems., • Graduate degree in CS, ML, or AI., • Cloud experience (AWS, GCP) and model deployment experience., • Experience with LLM evaluation, CV robustness, or RL validation., • Knowledge of interpretability, adversarial robustness, or AI safety frameworks., • Familiarity with ML evaluation frameworks and agentic model design. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Senior Computer Vision Scientist Fully Remote - HQ in New York, New York $190,000-210,000 base salary + equity THE COMPANY Harnham is partnering with an innovative health-tech startup building patient-focused agentic AI, multimodal computer vision and LLM applications to advance capabilities in medical claims and medical imaging in hospitals. The AI science team builds scalable, data-driven solutions that personalize user experiences and equip care providers with actionable insights, all while working with large-scale infrastructure and diverse technologies. THE ROLE • You will be responsible for computer vision and multimodal model research, building and development for the company's agentic AI product across imaging centers and hospitals, • You will report directly to senior leadership and work closely on technical direction, • Own applied AI research and quickly build into production, particularly focusing on novel AI, computer vision and LLM applications, • You will directly work with production team on implement and design code and build out to production using various machine learning, imaging and LLM techniques, owning machine learning modeling, • You will play an integral role of building out the AI team and scaling out its product, • Act as a thought leader role for AI across the business, mentoring junior team members YOUR SKILLS AND EXPERIENCE The successful Senior Computer Vision Scientist will likely have the following skills and experience: • 5+ years of commercial experience preferred with a focus on applied machine learning and computer vision research, building production-grade models with NLP and LLMs ideally with voice, image and multi-modal systems, • Experience working in a scaling startup is preferred, • Expertise in Python (TensorFlow, PyTorch) for production-grade work, • Commercial experience building novel AI platforms with large datasets, • History of working with and managing real-time AI applications in production settings, • Cloud experience in AWS, Azure or GCP, • DevOps exposure with CI/CD pipelines preferred, • History of working on models from concept to production / end-to-end / 0-1, • Applied research background in a commercial setting required, • Publication and/or patent history highly preferred, • Experience in settings wearing multiple hats, • Domain experience in healthcare, health-tech, med-tech or similar a plus; EHR, EMR, claims, HEOR or other medical data exposure highly preferred, • History of partnering with non-technical stakeholders required, • Experience owning projects, • PhD degree in Medical Imaging, Computer Science, Biomedical Imaging or similar THE BENEFITS A competitive base salary of $190,000-210,000 + benefits + equity HOW TO APPLY Please register your interest by sending your résumé to Tim Jonas via the Apply link on this page. KEYWORDS Machine Learning | AI | Artificial Intelligence | Technology | Applied Research | Health-tech | Healthcare | Medical | Startup | Deployment | Production | LLMs | LLM | Large Language Models | GenAI | Gen AI | Generative AI | Voice Bots | Chatbots | Natural Language Processing | EHR | Electronic Health | Electronic Medical | HEOR | Claims Data | Patient | Hospital | Docker | Kubernetes | Weights & Biases | PyTorch | TensorFlow | Publications | Patents | Computer Vision | Medical Imaging | MRI | Multimodal

About Child Mind Institute We're dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. We've become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments. Position Details: As part of the Center for Data Analytics, Innovation, and Rigor team, you will report to Technical Project Manager. You will will design and conduct advanced data analyses and develop machine learning models for use in mental health research. You will perform analyses on large datasets, collected using a range of multi-modal methods, including cognitive assessments (both paper-and-pencil and digitized formats), surveys, and other multimodal biometric modalities. You will be chiefly responsible for the design, documentation, and execution of experiments that advance our understanding of both existing data collection and assessment tools in the mental health space, as well as downstream analytic models that seek to apply these measurements.. This is an exempt, full-time, hybrid this position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor in our NYC headquarters office. The in-office requirement and schedule are subject to change based on the needs of the program and the organization. You Will: * Design and implement analytical workflows including data preprocessing, featureengineering, model development, scientific analyses, data visualization, andvalidation. * Contribute to effective, scalable, well-documented code that is suitable for highperformance computing ecosystems and shared to GitHub, or equivalent,repositories for version control. * Perform organization, aggregation, pre-processing, and analysis of large datasetsusing high-performance computing infrastructures. * Apply both pre-trained and custom-made machine learning models and datamanipulation pipelines to research and clinical contexts, ensuring the responsiblehandling of sensitive data. * Write documentation and text for scientific or public dissemination of knowledge andattend and present at meetings. * Assist with the definition of project and collaboration objectives, tasks, anddeliverables at the outset of new efforts, and support ongoing monitoring ofprogress and alignment. * Perform additional job-related duties as assigned You Have: * Bachelor's in Neuroscience, Psychology, Engineering, Computer Science orequivalent combination of education and experience. * 5+ years of experience in data analysis and data science fundamentals (e.g.,algorithms, data structures, data visualization, machine learning), preferably in aclinical or research setting. * 5+ years of experience including education in at least one scientific programminglanguage (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g.,Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required. * 3+ years of experience including education working in a Linux environment, usingversion control systems (e.g., GitHub), and software virtualization platforms (e.g.,Docker). * 3+ years of practical experience designing and developing ML and NLPtechnologies using ML and NLP toolchains (e.g., pytorch, tensorflow, SpaCy,HuggingFace, NLTK.) #LI-remote, #LI-on-site, #LI-hybrid. Our Benefits Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, discounted tickets and entertainment perks programs. For more information about our benefits, please visit our ___. Pay Range The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting. EEO Disclaimer Child Mind Institute is committed to fostering an inclusive and equitable workplace where all individuals are treated with respect and dignity. We are proud to be an equal opportunity employer and prohibit discrimination and harassment of any kind. We provide equal employment opportunities to all employees and applicants for employment, regardless of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity, gender expression, age, national origin, ancestry, citizenship status, marital status, military or veteran status, physical or mental disability, genetic information, medical condition, or any other characteristic protected by applicable federal, state, or local laws. In compliance with California law, we also prohibit discrimination based on reproductive health decision-making, status as a victim of domestic violence, sexual assault, or stalking, or any other category protected by the California Fair Employment and Housing Act (FEHA). In New York, we extend this prohibition to include status as a victim of domestic violence, familial status, or any other characteristic protected by the New York State Human Rights Law (NYSHRL). Child Mind Institute is dedicated to ensuring accessibility and reasonable accommodations for individuals with disabilities or medical conditions. If you require an accommodation to participate in the application process or perform your job, please contact our HR Department at ___ This policy applies to all aspects of employment, including recruitment, hiring, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, benefits, and training.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you'll work on building out the algorithms for our next-gen Agent RL training platform, support large scale training, and research and integrate state-of-the-art technologies to optimize our ML system. Your customer will be other MLREs and AAIs on the Enterprise AI team who are taking the training algorithms and applying them to client use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern AI movement, we would love to hear from you! You will: • Build, profile and optimize our training and inference framework., • Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements., • Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.., • At least 1-3 years of LLM training in a production environment, • Passionate about system optimization, • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc., • Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster, • Experience with multi-node LLM training and inference, • Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc., • Strong written and verbal communication skills to operate in a cross functional team environment. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations. About This Role This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions. Ideally, you'd have: * Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes. * A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.). * At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning. * Strong written and verbal communication skills, along with the ability to work effectively across teams. Nice to have: * Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX. * Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents. * Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar. * Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH. * Proficiency in cloud-based ML development, with experience in AWS or GCP environments. Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$252,000—$315,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes. Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research. If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you. You will: • Build and deploy multi-agent systems for agentic reasoning validation, • Develop pipelines to detect errors and scale human judgment, • Combine classical ML, LLMs, and multi-agent techniques for reliability, • Lead research into agent failure modes and ship fixes, • Use AI tools to speed prototyping and iteration, • Build data-driven evaluations and deploy rapid improvements, • PhD or MSc in Computer Science, Mathematics, Statistics, or related field, • 3+ years shipping scaled production ML systems, • Demonstrated real-world impact, • Mastery of PyTorch, TensorFlow, JAX, or scikit-learn, • Deep expertise in agentic LLMs and multi-agent systems, • Strong software engineering and microservices (AWS/GCP), • Rapid, data-driven iteration, • Proficiency using AI tools to accelerate work, • Strong research depth with practical bias, • Experience prototyping agent evaluation/reliability systems, • Human-in-the-loop or annotation pipeline work, • Open-source contributions in agents, evaluation, or alignment About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you'll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like ___ and ___, we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: • Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability., • Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data., • Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently., • Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets., • Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions., • Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts., • Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments., • Partner closely with engineering managers, product leaders, and researchers to scope high-impact initiatives and unblock execution across teams. Ideally You'd Have: • 8+ years of experience building and deploying applied ML systems in production environments., • Deep experience with agentic systems, autonomous workflows, or ML systems that reason and act over multiple steps., • Strong background in ML systems engineering, including model serving, pipelines, monitoring, and evaluation., • Hands-on experience with retrieval systems, embeddings, or representation learning., • Proficiency in Python and modern ML frameworks (ex: PyTorch), with the ability to design systems end to end., • Demonstrated ability to operate at Staff-level scope: setting technical direction, owning ambiguous problems, and driving 01 initiatives to production., • High ownership over 01 systems that move directly into production., • Real-world constraints that force thoughtful engineering tradeoffs, not just model tuning., • Opportunity to shape foundational agentic infrastructure used across multiple teams and missions. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Scale AI is seeking highly skilled and motivated Software Engineers to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in delivering high-impact AI-powered mission solutions for government customers. Our scalable and high-performance platform forms the foundation for these solutions, and your expertise will be instrumental in designing and implementing systems that can handle billions of data points with exceptional performance. You will: • Design and implement scalable backend systems for Federal customers, leveraging Scale's modern and cloud-native AI infrastructure, • Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments, • Develop distributed systems, data-intensive applications, and machine learning infrastructure to enable real impact for mission owners, • Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions, • Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions, • Contribute to the platform roadmap and product strategy for Scale AI's Federal business, playing a key role in shaping the future direction of our offerings, • This role will require an active TS/SCI security clearance or the ability to obtain a security clearance. Ideally you'd have: • Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases, • Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus, • Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles, • Machine Learning Infrastructure: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure. Understanding of model serving, monitoring, and deployment strategies is beneficial, • Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles, • Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Scale AI is seeking highly skilled and motivated Software Engineers to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in delivering high-impact AI-powered mission solutions for government customers. Our scalable and high-performance platform forms the foundation for these solutions, and your expertise will be instrumental in designing and implementing systems that can handle billions of data points with exceptional performance. You will: • Design and implement scalable backend systems for Federal customers, leveraging Scale's modern and cloud-native AI infrastructure, • Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments, • Develop distributed systems, data-intensive applications, and machine learning infrastructure to enable real impact for mission owners, • Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions, • Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions, • Contribute to the platform roadmap and product strategy for Scale AI's Federal business, playing a key role in shaping the future direction of our offerings, • This role will require an active TS/SCI security clearance or the ability to obtain a security clearance. Ideally you'd have: • Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases, • Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus, • Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles, • Machine Learning Infrastructure: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure. Understanding of model serving, monitoring, and deployment strategies is beneficial, • Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles, • Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

Scale's ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale's ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! • Build, profile and optimize our training and inference framework, • Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation, • Research and integrate state-of-the-art technologies to optimize our ML system, • Strong excitement about system optimization, • Experience with multi-node LLM training and inference, • Experience with developing large-scale distributed ML systems, • Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc., • Strong written and verbal communication skills and the ability tooperate in a cross functional team environment, • Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$218,400—$273,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

We are seeking a strategic, technically strong Director of Decision Science to lead our Data Science and Business Intelligence teams. In this role, you will set the vision, guide a high-performing team, and drive Data Science and BI initiatives that influence decisions across the business. You will partner with cross-functional leaders to solve high-impact problems, elevate our self-serve BI capabilities, and embed data science into core business operations. This role reports to the VP of Data & Analytics. What You'll Do * Vision and Strategy Leadership: Define and own the multi-year Data Science and BI strategy and roadmap, ensuring direct alignment with enterprise priorities and quantifiable business outcomes (e.g., revenue growth, operational efficiency) * Team Leadership & Development: Recruit, mentor, and manage a high-performing, multi-disciplinary team of Data Scientists, BI Analysts, and BI Engineers, establishing a culture of innovation, operational excellence, and continuous professional development * Strategic Business Partnership: Act as the primary analytic partner to business unit leaders (Sales, Product, CS, Marketing, etc.) to define and deliver high-impact, decision-support data products, including predictive models and AI-powered self-service insights * Analytical Translation: Translate complex, ambiguous business challenges into structured analytical strategies, guiding teams to deliver high-quality, decision-ready solutions * Agile Delivery & Model Lifecycle: Drive an agile, iterative delivery process and oversee end-to-end predictive model lifecycle management, from ideation and validation through scalable deployment, monitoring, and optimization * Executive Communication & Storytelling: Communicate clear, actionable, and data-driven recommendations to all audiences, including senior and executive leadership, shaping strategy through compelling, tailored narratives * Data Platform Collaboration: Collaborate closely with Data Engineering and Analytics Engineering to design and scale enterprise data assets, features, and metrics that meet evolving analytical needs * Governance & Responsible AI: Establish and enforce best practices for metrics design, experimentation, and data governance. Champion data ethics, compliance, and responsible AI standards to promote transparency and trust * Enterprise Data Strategy: Partner with leaders across Data Platform, Data Product Management, and Data Governance to develop and execute the overarching Enterprise Data Strategy What You'll Need Minimum Qualifications * 8+ years of experience in Data Science, Machine Learning, or related analytical fields, including 3+ years leading high-performing technical teams * Advanced degree (MS/PhD) in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, or similar) * Demonstrated ability to translate ambiguous business problems into analytical frameworks and deliver measurable business impact * Experience in SaaS or B2B environments, especially where data products directly enable go-to-market, customer success, or product strategy * Hands-on experience deploying and operating ML models in production, including monitoring, optimization, and lifecycle management Preferred Qualifications * Deep expertise in statistical modeling, causal inference, experimentation design, and applied analytics to drive business decisions * Strong familiarity with modern data ecosystems, including cloud data warehouses (Snowflake, BigQuery), data modeling best practices, orchestration tools, enterprise BI platforms (e.g., Looker, Tableau, Sigma), and MLOps/ML lifecycle platforms * Experience building or applying NLP, recommendation engines, forecasting models, or other advanced analytical solutions * Strong programming skills in Python and proficiency with modern ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) * Demonstrated ability to design, govern, and scale standardized metrics, dashboards, and self-service BI workflows across business functions * Exceptional communication and stakeholder-management skills, with the ability to influence senior leaders and simplify complex concepts for diverse audiences * Proven success in hiring, developing, and scaling technical talent across Data Science and BI disciplines Working Conditions & Travel Requirements * Ability to travel to meet with customers and/or key stakeholders, product teams in other Workiva locations (up to 25%) * Reliable internet access for any period of time working remotely, not in a Workiva office How You'll Be Rewarded Salary range in the US: $177,000.00 - $284,000.00 A discretionary bonus typically paid annually Restricted Stock Units granted at time of hire 401(k) match and comprehensive employee benefits package The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors. Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic. Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email ___. Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards. Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment. #LI-LP1

Job Description Summary This position will be located at the East Hanover, NJ location and will not have the ability to be located remotely. This is 1 of 2 roles. Job Description The Insights and Decision Science (IDS) team is dedicated to enabling improved decision making at Novartis by leveraging superior data to identify actionable insights that drive enhanced performance. We collaborate closely with the US business, bringing insights and challenging ideas to empower smarter, data-driven decision-making. Reporting into the ED, AI and Innovation Data Science, this role is crucial in leading the development and deployment of advanced AI solutions that enhance operational efficiency and drive strategic growth across the organization. This position plays a vital role in integrating AI-driven solutions across various platforms, fostering collaboration between the US commercial team and the India-based data science team. By championing the exploration of cutting-edge AI technologies, the Director ensures that our strategies are informed by the latest advancements in generative AI and large language models (LLMs). This role will collaborate with other members of the IDS AI and Innovation team members to create, pilot, and scale AI tools to support broader goals of the IDS strategy to transform business processes and outcomes. Key Responsibilities: • Lead the development and deployment of scalable AI solutions, focusing on advanced AI applications across various business units. Be prepared to engage in hands-on work when necessary to support the team and further our data science initiatives. * Collaborate with cross-functional teams to integrate AI-driven solutions across various platforms and services. * Drive innovation by staying current with advancements in AI, particularly in generative models and LLM technologies. * Champion the exploration and integration of cutting-edge AI technologies, particularly in the field generative AI. * Act as a key liaison between the US commercial team and the India-based data science team. * Stay abreast of state-of-the-art foundation models and other innovative trends in data science and leverage these insights to inform our strategies. * Bring a "can-do" attitude and teamwork and inspire others on culture change. * Acts as an AI role model, championing a culture that embraces cutting-edge AI technologies and encourages experimentation and adoption of best practices Experience: Novartis is seeking an individual with proven experience working with machine learning models. They should have a strong ability to support cross-team development of AI programs. A firm commitment to driving continuous improvement in AI solutions, informed by current innovations, is vital to this role. Essential Requirements: • Advanced degree in Computer Science, Engineering, Statistics, or related field Minimum of 10 years of experience in data science, with 6 years of experience in the pharmaceutical industryis preferred. * Build and deploy scalable machine learning models using cloud-based services such as AWS and Azure * Strong understanding of deep learning algorithms, foundational/ LLM models, statistics, and recommendation system * Deep knowledge of Large Language Models (LLMs) such as GPT, BERT, Cohere, and their applications in real-world scenarios. * Ability to operate in a hands-on capacity when necessary. * Proficient in programming languages such as Python, Spark, TensorFlow, and PyTorch * Experience with digital channel selection for "next best action" * Excellent problem-solving skills and ability to identify creative solutions to complex problems * Strong ability to effectively communicate and work across different time zones The pay range for this position at commencement of employment is expected to be between: $194,600.00 and $312,400.00 a year; however, while salary ranges are effective from 1/1/25 through 12/31/25, fluctuations in the job market may necessitate adjustments to pay ranges during this period. Further, final pay determinations will depend on various factors, including, but not limited to geographical location, experience level, knowledge, skills, and abilities. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility and reasonable accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message. Salary Range $194,600.00 - $361,400.00 Skills Desired Applied Mathematics, Artificial Intelligence (AI), Aws (Amazon Web Services), Big Data, Building Construction, Cloud Computing, Computer Science, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Electrical Transformer, Machine Learning (ML), Master Data Management, Professional Services, Python (Programming Language), R (Programming Language), Random Forest Algorithm, Statistical Analysis, Time Series Analysis

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we're accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale's Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions. • Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes., • A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.), • At least three years of experience addressing sophisticated ML problems, either in a research setting or product development., • Strong written and verbal communication skills and the ability to operate cross-functionally., • Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax., • Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents., • Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc., • Familiarity with agentic reasoning methods such as STaR and PLANSEARCH Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$275,000—$350,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers. Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like ___ and ___. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications. • Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers., • Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics, • Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines, • Work with massive datasets to develop both generic models as well as fine tune models for specific products, • Build scalable machine learning infrastructure to automate and optimize our ML services, • Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations, • Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment, • This role will require an active security clearance or the ability to obtain a security clearance., • Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment, • Solid background in algorithms, data structures, and object-oriented programming, • Strong programing skills in Python, experience in Tensorflow or PyTorch, • Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization, • Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments, • Experience with computer vision, generative AI models, large language models, or agentic systems About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

About Us At Selective, we don't just insure uniquely, we employ uniqueness. Selective is a midsized U.S. domestic property and casualty insurance company with a history of strong, consistent financial performance for nearly 100 years. Selective's unique position as both a leading insurance group and an employer of choice is recognized in a wide variety of awards and honors, including listing in Forbes Best Midsize Employers in 2025 and certification as a Great Place to Work in 2025 for the sixth consecutive year. Employees are empowered and encouraged to Be Uniquely You by being their true, unique selves and contributing their diverse talents, experiences, and perspectives to our shared success. Together, we are a high-performing team working to serve our customers responsibly by helping to mitigate loss, keep them safe, and restore their lives and businesses after an insured loss occurs. Overview "Applicants must be authorized to work for any employer in the United States. Selective will not sponsor or assume the sponsorship of an employment visa at this time". Note for NJ candidates: This role will be located at our future headquarters in Short Hills, N.J. Until the new headquarters is operational, the successful candidate will be offered the ability to work in our Branchville, N.J. location during this interim period. As Lead Software Engineer, you will drive technical direction and execution for robust, scalable, and maintainable enterprise software solutions within our cloud-first environment. You will champion engineering discipline by enforcing coding standards, architectural principles, and best practices throughout the development lifecycle. This role is pivotal in guiding engineers, conducting thorough code reviews, leading by example in modern engineering practices, and fostering a culture of continuous improvement and technical excellence. You will also architect and integrate AI-powered features using Azure AI Services, helping deliver intelligent solutions that align with our business objectives. Responsibilities • Lead the design, development, and deployment of cloud-native, full-stack applications with .NET and Azure, ensuring scalability, performance, and reliability., • Establish and enforce coding standards, design patterns, and architectural guidelines across software projects., • Champion best practices in automated testing, CI/CD pipelines, Infrastructure-as-Code (Terraform, Bicep, ARM), and rigorous documentation., • Architect and integrate AI capabilities using Azure AI Services (Cognitive Services, ML, OpenAI, Bot Services) for predictive analytics, NLP, and intelligent automation., • Conduct code reviews, provide constructive feedback, and mentor engineering talent in cloud-native, AI, and agile delivery practices., • Collaborate with product, QA, and cross-functional teams to clarify requirements, refine technical solutions, and deliver features aligned to business needs., • Continuously evaluate and adopt new technologies, tools, and methodologies to improve productivity, quality, and security., • Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline., • 7+ years of hands-on experience in software engineering and architecture, with deep knowledge of .NET (C#, ASP.NET Core) and Azure cloud services., • Advanced proficiency in Azure AI Services for developing and deploying enterprise AI-driven solutions., • Expertise in microservices, API-first design (REST/GraphQL), event-driven systems, and container orchestration (Docker, Kubernetes)., • Proficiency in DevOps, CI/CD, Infrastructure-as-Code, and Agile/Scrum/SAFe methodologies., • Strong code review, testing, problem-solving, and leadership skills., • Experience integrating AI features via REST APIs or SDKs into business applications., • Business Process Management (BPM) implementation experience, especially with Pega, is a plus., • Experience with Python, and familiarity with machine learning/deep learning frameworks such as TensorFlow and PyTorch., • Hands-on with additional BPM tools (Camunda, Appian)., • Front-end frameworks (Angular, React), advanced SQL, and data streaming technologies (Kafka, RabbitMQ)., • Knowledge of data privacy, compliance, and security requirements for cloud and AI adoption. Selective Insurance offers a total rewards package that includes a competitive base salary, incentive plan eligibility at all levels, and a wide array of benefits designed to help you and your family stay healthy, achieve your financial goals, and balance the demands of your work and personal life. These benefits include comprehensive health care plans, retirement savings plan with company match, discounted Employee Stock Purchase Program, tuition assistance and reimbursement programs, and 20 days of paid time off. Additional details about our total rewards package can be found by visiting our ___. The actual base salary is based on geographic location, and the range is representative of salaries for this role throughout Selective's footprint. Additional considerations include relevant education, qualifications, experience, skills, performance, and business needs. Pay Range USD $119,000.00 - USD $163,000.00 /Yr. Additional Information Selective is an Equal Employment Opportunity employer. That means we respect and value every individual's unique opinions, beliefs, abilities, and perspectives. We are committed to promoting a welcoming culture that celebrates diverse talent, individual identity, different points of view and experiences - and empowers employees to contribute new ideas that support our continued and growing success. Building a highly engaged team is one of our core strategic imperatives, which we believe is enhanced by diversity, equity, and inclusion. We expect and encourage all employees and all of our business partners to embrace, practice, and monitor the attitudes, values, and goals of acceptance; address biases; and foster diversity of viewpoints and opinions. For Massachusetts Applicants It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale's ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! • Build, profile and optimize our training and inference framework., • Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation., • Research and integrate state-of-the-art technologies to optimize our ML system., • Passionate about system optimization, • Experience with multi-node LLM training and inference, • Experience with developing large-scale distributed ML systems, • Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc., • Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc., • Strong written and verbal communication skills to operate in a cross functional team environment., • Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$252,000—$315,000 USD PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at . Please see the United States Department of Labor's ___ for additional information. We comply with the United States Department of Labor's ___. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our ___ for additional information.

About Child Mind Institute We're dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. We've become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments. Position Details: As part of the Center for Data Analytics, Innovation, and Rigor team, you will report to Technical Project Manager, you will lead the implementation and validation of evaluation frameworks for assessing both AI systems in clinical and mental health research contexts, and the symptoms of their users. You will own the distillation of clinical definitions into evaluation rubrics, combining applied clinical science with evaluation operations to ensure that rubrics are clinically grounded and operationally scalable. You will work closely with both the clinical and data science teams, ensuring knowledge is effectively operationalized to the satisfaction of both specializations. Supervising a small team of data science and software professionals, you will establish reliability standards, oversee the design of metrics for use in multi-rater evaluation systems, and ensure scientific rigor through quality assurance, versioning, and comprehensive documentation. This is a full-time, exempt position. A hybrid schedule will be required for employees based in the New York Tri-State area or California Bay Area, with a minimum of four (4) days per week in the office, on a schedule determined by your supervisor. Remote positions will be considered for candidates located outside of these regions . The in-office requirement and schedule are subject to change based on the needs of the program and the organization. Please note: We are not currently able to employ individuals residing in Ohio, North Dakota, Washington, or Wyoming. You Will: • Translate clinical symptom evaluations and manualized therapeutic protocols into reliable, consistent, precise, and scorable evaluation criteria., • Design and implement metadata standards and protocols for multi-rater clinical evaluation systems, enabling crowd-sourced ratings from diverse clinical experts., • Set reliability standards and adjudication logic for resolving disagreements among clinical annotators, ensuring consistency across large-scale annotation efforts., • Establish and enforce quality assurance processes, versioning systems, and comprehensive documentation for all evaluation rubrics and measurement frameworks., • Contribute to scientific publications, white papers, and technical documentation of measurement methodologies and validation studies., • Collaborate with clinical leadership to ensure evaluation criteria accurately reflects clinical best practices, safety standards, and clinician feedback., • Supervise and mentor a small team of data analysts and engineers, providing guidance on evaluation methodologies, statistical analysis, and rubric implementation., • Collaborate with other technical project stakeholders, to ensure that technical definitions and requirements of all curated rubrics and resources are being met. You Have: • PhD, PsyD, MD, or equivalent experience in measurement science, psychometrics, biostatistics, clinical psychology, epidemiology, or related field, • 8+ years of applied evaluation experience in clinical research, health outcomes research, or psychometric assessment, • 5+ years of experience with patient evaluation, clinical rating scales, or performance assessment frameworks, • 5+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required. Experience can be concurrent with education., • 5+ years of experience with applied statistics, including reliability analysis, classical test theory, item response theory, or factor analysis., • Demonstrated leadership of multi-rater or benchmark systems. #LI-hybrid #LI-remote Our Benefits Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, flexible work schedules, discounted tickets and entertainment perks programs. For more information about our benefits, please visit our ___. Pay Range The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting. EEO Disclaimer Child Mind Institute is committed to fostering an inclusive and equitable workplace where all individuals are treated with respect and dignity. We are proud to be an equal opportunity employer and prohibit discrimination and harassment of any kind. We provide equal employment opportunities to all employees and applicants for employment, regardless of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity, gender expression, age, national origin, ancestry, citizenship status, marital status, military or veteran status, physical or mental disability, genetic information, medical condition, or any other characteristic protected by applicable federal, state, or local laws. In compliance with California law, we also prohibit discrimination based on reproductive health decision-making, status as a victim of domestic violence, sexual assault, or stalking, or any other category protected by the California Fair Employment and Housing Act (FEHA). In New York, we extend this prohibition to include status as a victim of domestic violence, familial status, or any other characteristic protected by the New York State Human Rights Law (NYSHRL). Child Mind Institute is dedicated to ensuring accessibility and reasonable accommodations for individuals with disabilities or medical conditions. If you require an accommodation to participate in the application process or perform your job, please contact our HR Department at ___ This policy applies to all aspects of employment, including recruitment, hiring, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, benefits, and training.

The Simoncelli group in the Department of Applied Physics and Applied Mathematics at Columbia University invites applications for a Postdoctoral Research Scientist in theoretical-computational materials science. The successful candidate will advance research in the theoretical formalism and machine-learning simulation framework to describe coupled transport phenomena, involving electronic, spin, and vibrational excitations in energy materials with an arbitrary degree of atomic disorder. Experience in one or more of the following areas is highly valued: • First-principles and machine-learning-based simulation approaches for electronic and magnetic properties of materials., • Many-body Green's function formalism., • Coding (Python, C++, PyTorch) and parallel computing (MPI, OpenMP, CUDA, Kokkos)., • Experience in research communication through conference presentations and publications., • Ability to work well in a team and experience in mentoring students. The position is expected to begin on January 1, 2026, or as soon as possible thereafter. It is funded for one (1) year, renewable contingent on performance and funding. The priority deadline for applications is December 1, 2025; applications will continue to be accepted on a rolling basis until the position is filled. Expected Base Salary: $72,116; visit the link below for information about benefits Columbia University is an Equal Opportunity/Affirmative Action employer. We recruit, hire, and promote without regard to race, color, sex, gender, pregnancy, religion, creed, marital or partnership status, age, sexual orientation, gender identity or expression, national origin, disability, military/veteran status, or any other legally protected status. Columbia University provides reasonable accommodations to applicants with disabilities. To request an accommodation for the application process, contact the Office of Institutional Equity (212-854-5511, ). Required Qualifications: • A PhD in physics, computational materials science, or computer science, earned by January 1, 2026 or by start date. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

The Department of Biomedical Engineering - Prof. Elham Azizi's Lab, is looking for a Staff Associate III to: Functional Knowledge (35%) - Develop advanced probabilistic and causal generative frameworks linking molecular to clinical data; design interpretable representation spaces for tumor-immune dynamics and therapy response. Technical Expertise (25%) - Engineer LLM and diffusion/flow-matching pipelines; integrate multi-GPU distributed training, experiment tracking, and MLOps automation. Problem-Solving Skills (15%) - Innovate adaptive fine-tuning, multi-task learning, and agentic reasoning strategies to improve generalization and data efficiency. Decision Making/Autonomy (10%) - Lead architectural and data design decisions; prioritize experiments aligned with program milestones; evaluate trade-offs between model accuracy and interpretability. Communication Skills (10%) - Present findings at internal symposia and external conferences; co-author manuscripts; write high-quality documentation and technical reports. Mentorship/Leadership (5%) - Mentor junior engineers and research assistants; provide guidance on causal inference methods and AI-in-loop experimentation. B.S./B.E. (minimum) in Computer Science, Biomedical/Electrical Engineering, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications • Substantial expertise in training deep learning models and tuning large foundation models., • Expertise with developing efficient data loaders for large datasets and optimizing training workflows., • Deep knowledge of probabilistic modelling, self-supervised learning and representation learning, diffusion/VAE/flow matching architectures, • Strong Python, PyTorch/JAX, containerization & MLOps skills; familiarity with distributed training and modern experiment-tracking stacks, • Experience with AI coding tools (e.g., Copilot, Cursor) Preferred extras • M.S. or graduate-level degree in relevant field, • Experience with single-cell and spatial genomic or imaging data, and multimodal integration, • Expertise in statistical causal discovery and inference, • Publications or open-source contributions in generative models, • Strong interest in applications and driving impact in cancer biology and immunology 6+ years of experience in software engineering including: 3+ yrs hands-on experience training generative AI or large-language models at scale 2+ years experience with statistical or generative modeling Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

• Job Type: Short Term Casual, • Bargaining Unit:, • Regular/Temporary: Temporary, • End Date if Temporary:, • Hours Per Week: 10, • Standard Work Schedule: Mon - Fri 9am - 5pm, • Building: Columbia University Medical Center The Department of Surgery is seeking a Student Research Worker (CU Student). We are looking for a highly motivated master's-level computer science student with an interest in computer vision. The primary role will be to enhance an existing cardiac surgical video analysis pipeline by expanding anatomy recognition models to support AI-assisted surgery. Responsibilities • Maintain and augment the existing pipeline of surgical video analysis modules., • Develop a pipeline using Segment Anything 2 for semi-automated anatomy segmentation., • Aiding other module development relating to AI-assisted cardiac surgery., • High School Diploma or equivalent certificate. Undergraduate degree, graduate student (Master or PhD program) in computer science, with intermediate coding experience in Python. * Coding skills as above. Columbia University is committed to the hiring of qualified local residents.

Responsibilities: The Computational Biomarker Imaging Group (CBIG) has an open postdoctoral positions. CBIG's mission is to act as a translational catalyst between computational science and cancer imaging research. Work in our group focuses on developing innovative image analysis, machine learning, AI and data science methodologies for multimodality imaging, and also on incorporating such methods into clinically relevant applications. Most of our work to date has been on breast and lung cancer imaging, while more recently expanding more broadly in oncologic imaging and molecular imaging applications. A priority area is integrating imaging with genomic biomarkers towards integrated precision diagnostics for prevention and therapy for cancer. Applications focusing on radiomics and deep learning are also a priority. We are seeking highly motivated individuals with excellent academic track-record, including first-author publications in peer-reviewed journals. Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary research team. Salary range is from $75,000 - $85,000 The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Successful candidates should have, or be in the process of completing, a PhD (or equivalent) in Biomedical, Electrical or Computer Engineering, Computer and Information Science, Applied Mathematics, Statistics/Biostatistics, Bioinformatics, or related field. Ideal applicants should have a background on biomedical image analysis, computer vision, pattern recognition and/or machine learning. Experience with Bioinformatics is a plus. Proficiency in quantitative analytical methods and computer programming (e.g., Python, C/C ) is essential. Experience with medical image analysis (e.g., MRI, CT, X-ray, Ultrasound) and related statistical methods and software packages (e.g., ITK C/C libraries, R/SPSS) is desired (but not necessary). Experience with Deep Learning is also ideal (e.g., TensorFlow, Keras, PyTorch packages, etc.). Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

About Child Mind Institute We're dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. We've become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments. Position Details: As part of the Center for Data Analytics, Innovation, and Rigor team, you will report to Director, Center for DAIR. You will lead the coordination and execution of complex, large-scale AI research initiatives in mental health contexts. You will manage a team of approximately 10 data scientists and software engineers and collaborate closely with the Clinical Project Manager and project leadership, ensuring seamless collaboration and timely delivery of project milestones. You will oversee project planning, resource allocation, risk management, and stakeholder communication, using common project management tools and methodologies. This role requires strong project management expertise, technical fluency to communicate effectively with the engineering teams that will report to you, and the ability to navigate complex research environments while maintaining alignment with project objectives and organizational goals. This is a full-time, exempt position. A hybrid schedule will be required for employees based in the New York Tri-State area or California Bay Area, with a minimum of four (4) days per week in the office, on a schedule determined by your supervisor. Remote positions will be considered for candidates located outside of these regions . The in-office requirement and schedule are subject to change based on the needs of the program and the organization. Please note: We are not currently able to employ individuals residing in Ohio, North Dakota, Washington, or Wyoming. You Will: • Work with team members across management, multiple engineering teams, clinical researchers, and stakeholders to develop project plans, timelines, milestones, resource requirements and deliverables, all in alignment with the overall mission of the project and organization., • Guide the team through the entire product development lifecycle, from road mapping and requirements gathering, through prioritization and scoping (OKRs), delivery of designs, and project management of engineering execution., • Coordinate cross-functional teams including data scientists, AI engineers, software developers, clinical researchers, and external collaborators to ensure efficient workflow and communication., • Achieve consensus around product vision and priorities across product research, design, engineering, and data science along with our leadership team., • Monitor project progress, identify risks and bottlenecks, and implement mitigation strategies to keep projects on track and within budget., • Help design and implement clinical validation and quality assurance testing for data generation, annotation workflows, and software development to ensure scientific rigor and reproducibility., • Ensure data quality, security, and compliance with privacy regulations for handling sensitive data. You Have: • Master's in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience is required., • 8+ years experience in technical project management for software development, data science, or AI/ML research projects., • 8+ years of experience working regularly with software development lifecycle, data engineering, machine learning, or cloud computing concepts., • 5+ years of practical experience with project management tools and methodologies (e.g., Notion, Jira, Kanban)., • 5+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning)., • 5+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required., • Demonstrated experience managing complex, multi-phase projects in software development environments with multiple stakeholders and competing priorities. #LI-hybrid #LI-remote Our Benefits Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, flexible work schedules, discounted tickets and entertainment perks programs. For more information about our benefits, please visit our ___. Pay Range The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting. EEO Disclaimer Child Mind Institute is committed to fostering an inclusive and equitable workplace where all individuals are treated with respect and dignity. We are proud to be an equal opportunity employer and prohibit discrimination and harassment of any kind. We provide equal employment opportunities to all employees and applicants for employment, regardless of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity, gender expression, age, national origin, ancestry, citizenship status, marital status, military or veteran status, physical or mental disability, genetic information, medical condition, or any other characteristic protected by applicable federal, state, or local laws. In compliance with California law, we also prohibit discrimination based on reproductive health decision-making, status as a victim of domestic violence, sexual assault, or stalking, or any other category protected by the California Fair Employment and Housing Act (FEHA). In New York, we extend this prohibition to include status as a victim of domestic violence, familial status, or any other characteristic protected by the New York State Human Rights Law (NYSHRL). Child Mind Institute is dedicated to ensuring accessibility and reasonable accommodations for individuals with disabilities or medical conditions. If you require an accommodation to participate in the application process or perform your job, please contact our HR Department at ___ This policy applies to all aspects of employment, including recruitment, hiring, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, benefits, and training.

Join the team leading the next evolution of virtual care. At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives. Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens. Summary of Position The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime. This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment. The ideal candidate combines: • Strong security engineering and cloud architecture experience, • Deep, current familiarity with modern AI/LLM tooling and practices, • Familiar and can cover basic coding within the AI tooling space (python, others), • The ability to communicate clearly with senior leadership and influence enterprise-wide strategy Essential Duties and Responsibilities Secure AI / ML platforms and workloads • Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications., • Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads., • Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation., • Partner with data science and MLOps teams to harden:, • Data ingestion and labeling, • Training and fine-tuning pipelines, • Model registries and deployment workflows, • Inference APIs, agents, and integrations, • Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture. AI use case intake & governance • Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization., • Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards., • Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle., • Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams., • Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies. Monitoring, detection & assurance • Establish and maintain monitoring and detection for AI-specific threats, such as:, • Prompt injection and jailbreak attempts, • Data exfiltration and sensitive data exposure, • Misuse or abuse of AI tools and agents, • Anomalous model or pipeline behavior, • Integrate AI/ML systems with existing logging, SIEM, and incident response processes., • Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification. Strategy, leadership & enablement • Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk., • Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments., • Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress., • Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems. Qualifications Expected for Position • 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems., • 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems., • Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries., • Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring., • Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred., • Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption., • Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership. Preferred Qualifications: • Practical experience securing LLM- and genAI-based systems, such as:, • RAG architectures backed by internal data, • AI assistants, copilots, or agents integrated with enterprise tools, • Fine-tuned models and model hosting platforms, • Experience with AI IDE tools, • cursor, windsurfer, others, • Knows the security problems and has practical solutions that balances innovation with innovation., • Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools)., • Experience with:, • Security for data pipelines, feature stores, and model registries, • Detection engineering or SIEM tuning for AI-related events, • Red-teaming or adversarial testing of AI systems, • Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks)., • Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports., • Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus., • Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape., • High level of integrity and ethical conduct. This role is a fit if you: • Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects., • Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems., • Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation., • Can move fluidly between deep technical discussions and concise, executive-level explanations. This role is not a fit if you: • Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work., • Do not actively engage with current AI/LLM tooling, research, and emerging practices., • "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?", • "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?", • "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?" The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: ___.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions. We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details. As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified. Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future. Why join Teladoc Health? * Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our ___. * Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference. * Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day. * Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways. * Enjoy an inclusive ___ centered around you and your family, with tailored programs that address your unique needs. * Explore ___ with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on ___. As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind. Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available ___.

What we're looking for:** - Professional experience in machine learning model development, Python & ML frameworks (PyTorch/TensorFlow), model deployment & MLOps - Strong communication skills - Ability to work independently in a remote environment How it works: This is not a specific job posting.

Lead AI Engineer (MLX) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. Please note that this salary information is solely for candidates hire

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:. Master's or doctoral degree in computer science, electrical engineering, mathematics, or a si

Lead Machine Learning Engineer (Gen AI, Python, Go, AWS) As a Capital One Machine Learning Engineer (MLE) on the GenAI Workflows Serving team, you'll be part of an Agile team dedicated to designing, building, and productionizing Generative AI applications and Agentic Workflow systems at massive scale. You'll participate in the detailed technical design, development, and implementation of complex machine learning applications leveraging cloud-native platforms. You'll focus on building robust ML serving architecture, developing high-performance application code, and ensuring the high availability, security, and low latency of our Generative AI solutions. You will collaborate closely with multiple other AI/ML teams to drive innovation and continuously apply the latest innovations and best practices in machine learning engineering. What you'll do in the role The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and deliver GenAI models and components that solve complex business problems, while working in collaboration with the Product and Data Science teams. Design and implement cloud-native ML Serving Platforms leveraging technologies like Docker, Kubernetes, KNative, and KServe to ensure optimized and scalable deployment of models. Solve complex scaling and high-availability problems by writing and testing performant application code in Python and Go-lang, developing and validating ML models, and automating tests and deployment. Implement advanced MLOps and GitOps practices for continuous integration and continuous deployment (CI/CD) using tools like ArgoCD to manage the entire lifecycle of models and applications. Leverage service mesh architectures like Istio to manage traffic, enhance security, and ensure resilience for high-volume serving endpoints. Retrain, maintain, and monitor models in production. Construct optimized, scalable data pipelines to feed ML models. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Go, Scala or Java Bachelor's Degree At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, Go or Java At least 2 years of experience building, scaling, and optimizing ML systems Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models 2+ years of people leader experience 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead Machine Learning Engineer McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer New York, NY: $215,200 - $245,600 for Lead Machine Learning Engineer San Francisco, CA: $215,200 - $245,600 for Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Bachelor's Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer New York, NY: $176,500 - $201,400 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead AI Engineer (Gen AI Platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications [choose correct set based on focus of role]: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B parameters, 500B tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Publications studying tokenization, data quality, dataset curation, or labeling Contribution to a major open source corpus Contribution to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II Cambridge, MA: $262,500 - $299,600 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $193,400 - $220,700 for Lead AI Engineer McLean, VA: $193,400 - $220,700 for Lead AI Engineer New York, NY: $211,000 - $240,800 for Lead AI Engineer San Francisco, CA: $211,000 - $240,800 for Lead AI Engineer San Jose, CA: $211,000 - $240,800 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead AI Engineer (FM Hosting, LLM Inference) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher I (Multi-agent Systems, Knowledge Graphs/GraphRAG/Graph-of-Thought / GoT, MCP, LangGraph, Agent Protocols) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. The AI Foundations – AI Software Engineering team builds scalable, state-of-the-art AI architectures designed to transform the software development lifecycle at Capital One. Our goal is to empower internal engineers by developing multi-agent solutions that streamline design, code generation, system migration, and troubleshooting to operate software more effectively at scale.To achieve this, we leverage a cutting-edge stack including LangGraph, MCP, Knowledge Graphs, agent-to-agent protocols, and advanced model customization. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B parameters, 500B tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Agentic AI Research PhD focused on multi-agent systems, autonomous agents, planning, or reinforcement learning Hands-on experience developing and deploying multi-agent architectures (e.g., using frameworks like LangGraph or specialized agent protocols) Experience with techniques like tool-use integration, memory management for agents, or verifiable agent behavior Knowledge Graph Research PhD focused on knowledge representation and reasoning, graph neural networks (GNNs), or large-scale data integration Publications in relevant venues (e.g., ISWC, WWW, KDD, Neurips, ICML) on knowledge graph construction, embedding, querying, or reasoning Experience in designing, implementing, and deploying industrial-scale Knowledge Graph solutions Demonstrated expertise with graph databases (e.g., Neo4j, JanusGraph) and graph embedding techniques Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead AI Engineer (GenAI Platform Services) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you’ll do in the role: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams. Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor’s Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1 years of experience building, scaling, and optimizing ML systems 1 years of experience with data gathering and preparation for ML models 2 years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3 years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3 years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer New York, NY: $176,500 - $201,400 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

A leading AI technology company in Seattle seeks a Machine Learning Research Scientist/Engineer to transform research ideas into prototypes.Candidates should have practical experience with large language models (LLMs) and proficiency in frameworks like PyTorch, TensorFlow, or JAX.This full-time role

Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems Proficiency in Python and comfort with at least one systems language (e. We’re looking for a highly motivated engineer with experience deploying machine learning algorithms t

Job Description Company Overview: TrueGrowth is a forward-thinking company committed to empowering organizations with cutting-edge AI solutions. Our team thrives on innovation, collaboration, and a passion for transforming ideas into impactful technology. We are looking for an AI Engineer to help us shape the future of intelligent systems. Position Summary: As an AI Engineer, you will design and implement advanced AI models and algorithms that drive our products and services. Youll work closely with data scientists and product teams to develop solutions that leverage machine learning, natural language processing, and more. How to Apply: If youre ready to push the boundaries of AI technology, we want to hear from you! Please send a message on Instagram to @genomiller26! Key Responsibilities: * Design and develop AI models and algorithms to solve complex problems. * Collaborate with cross-functional teams to integrate AI capabilities into existing products. * Analyze large datasets to extract insights and improve model performance. * Stay current with industry trends and advancements in AI technology. Qualifications: * Strong experience in machine learning frameworks (TensorFlow, PyTorch, etc.). * Proficiency in programming languages such as Python, Java, or C++. * Familiarity with natural language processing and computer vision techniques. * Excellent problem-solving skills and a passion for AI innovation. Why Join Us? * Flexible Work Environment: Enjoy the freedom of remote work while engaging in groundbreaking AI projects. * Growth Opportunities: We believe in nurturing talent. Optional career coaching services are available to support your professional development at no risk—if you dont find it beneficial, theres no obligation to continue. * Dynamic Team Culture: Be part of a team that values creativity and collaboration, where your contributions are pivotal to our success. How to Apply: If youre ready to push the boundaries of AI technology, we want to hear from you! Please SEND A MESSAGE on Instagram to @genomiller26!

Job Description About VantageScore At VantageScore we drive impact for good on a massive scale impacting tens of millions of people across the United States. Our mission is to be the leading credit modeling company delivering the most predictive, most innovative, and most inclusive tri-bureau models and attributes in the US market. Our innovation is increasing access for millions more Americans to financial products and homeownership. Our models are among, if not the most, inclusive in the United States and power billions of credits scores a year. We are fueled by a growing, exceptionally talented team and are actively seeking individuals who can join us in driving us toward our ambitious goals. At VantageScore, you'll have the unique opportunity to work within a fast-paced, independent start-up culture while enjoying the financial stability that comes from being backed by the three leading US credit bureaus. VantageScore® consumer credit scoring models combine the need for both financial inclusion and dependable predictiveness across all scoring ranges. An industry thought leader and technology innovation leader, the company's most recent models score approximately 94 percent of all adults 18 and older - including 33 million more people than conventional models - without sacrificing safety and soundness. As a result, lenders using VantageScore can extend credit to those who have been historically marginalized, including minority and lower-to-middle-income Americans. VantageScore credit scores are used by over 3,700 banks, fintechs and other companies use VantageScore credit scores every day to assess consumer creditworthiness. Last year, over 42 billion VantageScore credit scores were used representing a 55% yearly increase. All 10 US banks use VantageScore credit scores or digital tools in one or more line of business. Starting in 2025 the FHFA has required VantageScore credit scores to be used for all mortgages sold to, or guaranteed by, Fannie Mae and Freddie Mac. Get started using VantageScore credit scores today - we are the leader in predictive power and financial inclusion. About The Role We are seeking a highly motivated and innovative Senior Data Scientist (AI/ML) to join our brilliant team of analytics professionals and developers, supporting the cutting-edge development of credit scoring models, generation of unique insights, and delivery of transformative technologies rooted in innovative value propositions. In this role, you will be essential to credit score model innovation, credit and open banking related research initiatives, pilot program analyses with lenders and fintech partners, and ongoing model monitoring and reporting processes. You'll bring your expertise in AI/ML and GenAI/Large Language Models (LLMs) to advance our use of structured and unstructured data to deliver new products and insights. You'll partner cross-functionally to deliver scalable AI-powered products and solutions that redefine how consumers engage with credit - ensuring our models are accurate, explainable, and aligned with our mission to empower responsible lending and financial inclusion. Key Responsibilities • Conduct advanced research on structured and unstructured data, developing insights to support product management and new product development., • Contribute to the design, development, evaluation, and deployment of machine learning (ML) models, including credit risk and predictive models., • Serve as the team's expert on GenAI/LLMs, adapting and fine-tuning models and ensuring explainability and compliance., • Drive pilot program analyses, including back-testing, rejection inference, and performance analyses using diverse data sets., • Improve and maintain existing model monitoring processes and develop compelling data visualizations and dashboards to communicate key insights to stakeholders., • Partner with engineers to operationalize models into production systems, ensuring scalability and resilience at high data and inference volumes., • Research and apply emerging AI/ML, GenAI/LLM technologies, staying abreast of state-of-the-art methods, tools, and best practices., • Translate complex analyses into clear, actionable business recommendations for both technical and non-technical audiences., • Master's or PhD degree in a quantitative field (e.g., Data Science, Applied Mathematics/Statistics, Computer Science, Engineering, Econometrics)., • A minimum of 5 years of professional experience in advanced analytics, AI/ML/LLM, and data science in research and/or corporate environments., • Proficiency in Python for data science and machine learning workflows., • Proven experience with machine learning techniques (classification, clustering, regression, neural networks) for predictive risk and credit modeling., • Strong track record of conducting research, developing analyses, and producing clear and impactful presentations or publications., • Experience delivering insights and solutions that drive business impact., • Deep expertise in GenAI - Natural Language Processing (NLP) and Large Language Models (LLMs) - including training, fine-tuning, explainability, and deployment., • Deep expertise in advanced ML techniques (self-supervised learning, training optimization, explainability) with focus on credit scoring., • Proficiency with modern ML/AI technology stack, such as PyTorch, AWS and related tools., • Experience delivering innovative, scalable AI/ML solutions integrated into production platforms., • High-level analytical problem-solving ability, with creativity in defining and solving ambiguous problems., • Exceptional communication skills, able to convey technical concepts to diverse stakeholders., • Salary Range: 150K Base + Bonus Are you a Senior Data Scientist who thrives on innovation and has a deep passion for fintech? We invite you to take the leap and join our team. Together, let's embark on a mission to redefine the industry and propel your career to new heights at VantageScore!

Job Description About Synaptrix Labs Inc. Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive approaches. We believe that the power to diagnose and treat neurological conditions safely, and to expand human potential, will become a reality with the right fusion of deep learning, signal processing, and computational neuroscience. We're seeking passionate, creative, and technically driven interns to join our team across multiple disciplines: Software Engineering, Hardware Engineering, Machine Learning Research, Industrial Design, and UI/UX Design. If you're excited about building the future of brain-computer interfaces and want to work at the intersection of neuroscience, AI, and human experience, we want to hear from you. Responsibilities: Depending on your background and interests, you may: • Contribute to development of real-time software systems for neural signal processing and data visualization., • Build and prototype non-invasive EEG-based BCI hardware, from electrode arrays to embedded microcontroller systems., • Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement., • Develop intuitive interfaces and user experiences for individuals with mobility or communication impairments., • Collaborate with the design team to prototype wearable and ergonomic form factors for next-generation neurotech devices., • Support data collection and analysis in research sessions, assisting with experimental setup and instrumentation., • Participate in cross-functional design reviews and brainstorming sessions that bring together neuroscience, AI, and engineering., • Currently pursuing a Bachelor's or Master's degree in Computer Science, Electrical Engineering, Biomedical Engineering, Neuroscience, Mechanical/Industrial Design, or a related field., • Demonstrated experience with one or more of the following:, • Software: Python, C++, or JavaScript, • Machine Learning: PyTorch, TensorFlow, or JAX, • Hardware: Arduino, PCB design, or embedded systems, • Design: Figma, Fusion 360, SolidWorks, or similar tools, • Strong problem-solving ability and curiosity about neuroscience, AI, or human-machine interfaces., • Excellent communication and teamwork skills; thrives in a fast-paced, interdisciplinary environment., • Prior experience with EEG/EMG systems, biosignal acquisition, or data analysis., • Familiarity with deep learning for time-series or multimodal data., • Experience designing assistive devices, wearables, or medical technology., • Portfolio, GitHub, or research projects demonstrating creative technical work. At Synaptrix Labs, we celebrate curiosity, open collaboration, and scientific rigor. Our interdisciplinary team spans neuroscience, AI, and clinical research, and we are united by the belief that non-invasive BCI is the key to unlocking a new era in healthcare, accessibility, and human augmentation. As an intern, you'll work directly alongside engineers, researchers, and designers who are defining the next generation of brain-computer interfaces. You'll be encouraged to explore bold ideas, experiment freely, and take ownership of meaningful projects from day one. What We Offer: • Hands-on experience in one of the world's most exciting emerging fields: brain-computer interfaces, • Opportunity to contribute to technology that directly improves lives, • Mentorship from scientists, engineers, and founders building real neurotechnology products, • Dynamic NYC workspace blending lab, workshop, and creative studio environments, • Potential for full-time conversion after graduation

Job DescriptionCompany Description Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through fourteen professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Job Description The Applied Analytics program is seeking data analytics professionals to serve as a part-time Associate for a graduate-level course called Applied Deep Learning and AI. This advanced course delves into deep learning, blending key elements from Statistical Machine Learning. Students will gain a solid foundation in supervised learning and other related algorithms and methods. Topics covered include Support Vector Machines, Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures, Generative Adversial Networks (GAN), and Reinforcement Learning. Practical applications will demonstrate how to prepare, train, test, and validate models. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University. Responsibilities • Attend all on-campus class sessions, assist with instruction, lead breakout sessions, facilitate discussions., • Evaluate, grade student work and assessments as requested by the course Lecturer., • Monitor and address student concerns and inquiries, • Conduct office hours.Qualifications Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements • Graduate degree in Computer Science, Data Science, or a related field (Completing relevant coursework such as Deep Learning, Machine Learning, and Statistics courses)., • Proficient in Python and familiar with deep learning frameworks (e.g., TensorFlow, PyTorch)., • Deep Learning Knowledge: Strong understanding of CNNs, RNNs, LLMs, Reinforcement Learning, and model evaluation techniques., • Hands-on experience with deep learning projects and data manipulation., • Strong verbal and written skills for explaining concepts clearly., • University teaching experience in related subjects Additional Information Please submit a resume inclusive of university teaching experience. All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity/Affirmative Action employer.

Job Description At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries, including financial services (particularly capital markets and fixed income), insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. Our solutions power trading desks, portfolio optimization, and risk analytics across fixed income, derivatives, and structured products. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As the Staff Machine Learning Engineer (VP) on the AI Science team, you will be responsible for architecting and deploying cutting-edge ML systems that power core business functions across the enterprise. Reporting to the Executive Director of AI Science, you will play a critical role in driving the development of scalable ML infrastructure, production-grade models, and reusable frameworks that deliver measurable business outcomes—ranging from cost optimization to top-line growth. You will bridge quantitative research and technology, with deep understanding of fixed income markets and derivatives. You will act as a technical thought leader and strategic partner in shaping the direction of the organization’s machine learning investments, fostering a culture of rigorous experimentation, reproducibility, and responsible AI. Key Responsibilities: • Design and deploy ML systems that solve high-impact business problems for critical workflows., • Develop and implement advanced ML methods including time series forecasting, reinforcement learning, optimization algorithms, and probabilistic modeling., • Lead the adoption of emerging ML techniques and tools (e.g., generative AI, LLM fine-tuning, vector databases, RAG) through rapid prototyping., • Partner with AI researchers and data scientists to translate experimental models into production-ready systems, supporting scaling and generalizability across business domains., • Own the development of foundational models and platform capabilities that serve as building blocks for downstream AI applications across the organization., • Ensure ML models are designed with safety, fairness, and transparency in mind, and aligned with internal governance frameworks and external regulatory standards., • Collaborate with cross-functional leaders in engineering, product, and business teams to embed ML-driven decision-making into core processes and workflows., • Continuously evaluate emerging ML techniques and tools, and champion their adoption through rigorous prototyping, benchmarking, and knowledge sharing., • Define and manage metrics to evaluate model performance and business impact, ensuring ML projects meet both scientific and operational standards., • Design ML-driven pricing models for fixed income securities, derivatives, and structured products., • 8+ years of experience building and deploying machine learning systems in production environments, preferably in investment banking, fixed income trading, or hedge funds, ideally within enterprise or platform-scale settings., • Proven track record of leading ML projects from ideation to production, including cross-functional collaboration and technical ownership., • Deep expertise in supervised, unsupervised, reinforcement learning or statistical modeling., • Experience with multimodal, generative AI, or large language models (e.g., LLMs, diffusion models) is a strong plus., • Proficiency in Python, along with modern ML and data stack tools (e.g., TensorFlow, PyTorch, scikit-learn, JAX, Ray, MLflow)., • Hands-on experience with MLOps principles and frameworks (e.g., CI/CD pipelines for ML, model monitoring, reproducibility)., • Strong understanding of cloud-based ML infrastructure (e.g., AWS SageMaker, GCP Vertex AI, or similar)., • Exceptional communication and collaboration skills, with the ability to translate technical details into strategic decisions., • Strong foundation in fixed income analytics, derivatives pricing, and risk management., • Commitment to responsible AI, including model fairness, transparency, and compliance with regulatory standards., • Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related discipline preferred. Preferred, but not required: • Hands-on experience with Palantir platforms (e.g., Foundry, AIP, Ontology) - including developing, deploying, and integrating machine learning solutions within Palantir’s data and AI ecosystem. Position Location This is a hybrid position based out of our New York, NY office. Compensation The base pay for this position is $290,000-300,000. A bonus will be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.