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Job Description About Us Daat Lab is an AI venture studio that collaborates directly with businesses to transform deep domain expertise into valuable, commercial-grade AI products. We assist companies in identifying and validating high-impact, AI-feasible use cases. Our process spans from initial ideation and building a proof of concept to developing a fully commercializable product and successfully launching it in the market. We maintain an active presence across multiple sectors, including real estate, digital marketing/e-commerce, and health, with an ambitious goal of adding one new product to our portfolio every month. About the Role We are seeking a Technical Lead to drive product development from initial concept to launch, maintaining a strong customer focus. This is a highly hands-on role where you will thrive in ambiguity and be responsible for the full product lifecycle across multiple projects simultaneously. You will collaborate directly with our strategy and business teams to identify high-value, AI-feasible opportunities and influence product direction through rapid execution, including discovery, prototyping, building, shipping, and iteration. What You’ll Do: • Own multiple projects from end to end: brainstorming product concepts, generating POCs to be evaluated and owning builds to reach a minimum viable product., • Build full-stack applications (backend, frontend, data layer, infra, deployment, and monitoring)., • Experiment with AI functionality on each case: classical ML when needed (forecasting, scoring, classification), plus LLM/agent workflows and evaluation loops, • Establish engineering standards: code quality, CI/CD hygiene, logging/analytics, basic security, • Work directly with design partners and ship weekly updates, • You should have:, • 6+ years shipping full-stack products end-to-end, • Strong Python and modern web stack (React/Next.js + APIs + DB + deployments), • Data processing and Machine learning fundamentals (pandas, Sklearn, pytorch/tensorflow, model evaluation), • Experience building with LLMs and Agent frameworks (Open AI SDK, Google ADK, Langchain/Langraph, MCP), • Comfort with ambiguity, fast cycles, and customer-facing iteration, • Team leadership experience (manager/tech lead), • What Success Looks Like:, • Ship multiple POCs that clearly validate feasibility and ROI, • Bring at least one concept to a usable MVP with design-partner feedback loops, • Salary: $160 - 200k (full-time hire, will start as a 1099 contractor) Please note: Daat Lab is a separate entity, unrelated to Alchemy Worx.

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Generative AI Research Scientist, you'll work alongside our founders and team members to develop advanced generative models that can synthesize and design biological systems at multiple scales. Building upon our biological reasoning model, you'll focus on creating the generative capabilities that turn insights into innovations. * ⁠You will design and develop cutting-edge generative models specifically for biological data, creating AI systems that can generate novel molecular structures, protein designs, cellular components, and biological pathways. * You will design and implement state-of-the-art generative algorithms including diffusion models, language diffusion models, diffusion transformers, and flow matching approaches and tailor them to biological constraints and properties * You will train and scale innovative AI models using large, diverse biological multi-modal datasets across distributed GPU clusters. * You will solve challenging AI research problems at scale, tackling key aspects such as model architecture and scaling, pre-training and fine-tuning strategies, and rigorous evaluation methods. * Your work will span various advanced generative AI architectures, including transformers, diffusion models, and autoencoders, exploring and implementing these techniques to push the boundaries of biological AI. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You have extensive hands-on experience building and training generative models, such as diffusion models, GANs, VAEs, normalizing flows, or autoregressive models. * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects. * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description About the Role: We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health. You will play a crucial part in delivering actionable insights and solutions to our clients, and your work will be integral to our mission. Responsibilities include but are not limited to; • ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health., • Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization., • Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training., • Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement., • Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs., • Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products., • Master's or Ph.D. in a related field with a strong academic background., • Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models., • Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning., • Proficiency in data manipulation, feature engineering, and model evaluation., • Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn., • Excellent communication skills and the ability to collaborate effectively within cross-functional teams., • A passion for continuous learning and staying updated with the latest trends and technologies in data science., • Strong problem-solving abilities and the capacity to translate complex data into actionable insights. Required knowledge of: • Python, • SQL, • Cloud Platforms (GCP, AWS, Azure), • Data Warehouses (BigQuery, Snowflake, Redshift), • LLMs / AI APIs, • Git / GitHubNice to have:, • Data Transformation (dbt), • Semantic Layers (Cube, Looker, dbt Metrics), • TypeScript, • Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics., • Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement., • Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures., • Nice to have - familiarity with adstock/saturation curves and budget optimization Our interview process includes, but is not limited to the following: • Unlimited vacation policy, • Monthly Phone Stipend, • Comprehensive Medical, Dental, and Vision insurance options, • 401(K) plan with matching, • Dog friendly office, • Hybrid work opportunity, • Professional Development Program Level 1 - Possesses essential capabilities * $145,057-$175,256 * Level 2 - Possesses developing capabilities * $175,256-$205,456 * Level 3 - Possesses notable capabilities. * $205,456-$235,655 * Level 4 - Possesses strong capabilities. * $235,655-$265,855 * Level 5 - Possesses advanced capabilities. * * $265,855-$296,054 About WITHIN & Brkfst.io WITHIN is the world's first Performance Branding company, partnering with some of the biggest brands in the world to drive business growth through innovative marketing strategies. Our integrated operating model collapses the traditional marketing silos between creative and media, performance and brand, and across media channels. With a full suite of offerings including media, creative, SEO, Lifecycle, Retail Media, Affiliate and Influencer, we're able to work with our brand partners in an integrated fashion, allowing us to align marketing strategies back to core business objectives. Client teams at WITHIN are trained on how to always act as a trusted business partner, acting as a fiduciary to client needs above our own. Teams at WITHIN have the ability to work with iconic brands such as The North Face, Timberland, Ben and Jerry's and Jose Cuervo. Everyone at WITHIN wants to grow and be challenged. It's a collaborative place made up of small, closely knit and versatile teams that are fast and adaptive to solve problems and build systems. Check out some of our work! Brkfst.io is an incubated venture within WITHIN, focused on connecting creators with major brands to produce impactful ads at scale. We are, and we connect creators with big brands to make impactful ads at scale. We have a network of thousands of content creators with a variety of different skill-sets, and we're looking to build a program that empowers them to create great ads for brands like Corkcicle, Perfume.com, Casper Mattresses, & more! This is a very ambitious project and our roadmap is full of exciting features, so we're looking for people who love innovation and want to be challenged. We're a small team of scrappy individuals who are growing fast, and we're looking for someone to grow with us. We weave AI into everything we do, using the latest tech across all teams to innovate, work smarter, and make better decisions. Whether it's in creative, operations, or anything else, AI helps us level up and do things at a whole new scale. We expect our people to use AI in their daily work, fully embracing it as a critical tool to help us succeed. Join Our Network! Stay connected with us and be the first to know about new opportunities, industry insights, and updates. Follow us on: • LinkedIn, • WhatsApp Community, • Instagram, • New York City: 43-01 22nd St, Suite 602, Queens, NY 11101, United States, • Bogotá: WeWork Av. Carrera 19 #100-45 Usaquén, Piso (Floor) 10, Bogotá, Distrito Capital de Bogotá 110111, Colombia, • Mexico City: Av. Paseo de la Reforma 296, Piso (Floor) 25, Oficina 111, Ciudad de México, CDMX 06500, México

Job Description:\n\nAbout Phaidra Phaidra is building the future of industrial automation. The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades. Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time. Specifically:We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data into high-value actions and decisions.We focus on industrial applications, which tend to be well-sensorized with measurable KPIs — perfect for reinforcement learning.We enable domain experts (our users) to configure the AI control systems (i.e. agents) without writing code. They define what they want their AI agents to do, and we do it for them. Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with DeepMind's AlphaGo, to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact. Phaidra's ability to achieve its mission is determined by our ability to work together — as defined by our core values: Transparency, Collaboration, Operational Excellence, Ownership, and Empathy. We seek individuals who embody these values, as they are instrumental in ensuring our team consistently delivers excellence and fosters an engaging and supportive culture Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, UK, Sweden, Spain, Portugal, the Netherlands, Singapore, Australia, and India.The Opportunity At Phaidra, security is the bedrock of trust for our customers operating the world's most critical infrastructure. We are looking for a Senior Product Security Engineer to partner directly with our Agentic AI department. This team is at the forefront of our mission, building autonomous agents responsible for optimizing the operational fabric of AI factories. These agents don't just chat; they act. They make real-time decisions to optimize power usage, cooling efficiency, and hardware health, creating a more stable and efficient environment for massive-scale compute. This is a high-stakes environment where the integrity and security of AI-driven decisions are paramount. You will tackle the unique security challenges of deploying autonomous agents that interact directly with physical control systems. Security failures here don't just mean data leaks; they could mean operational downtime or physical degradation of critical hardware. We need a security expert who thrives working hand-in-hand with AI researchers and engineers. Your role is to embed security into the DNA of our Agentic platform, ensuring that as our agents learn and explore, they do so within unbreakable safety boundaries. We are seeking a team member located in the following areas: UK or US (central and eastern time preferred)ResponsibilitiesChampion Secure Agentic AI Development: Drive the adoption of Phaidra's Secure AI/ML Development Lifecycle (SAIDL) within the Agentic AI team. Adapt security practices to fit the iterative and experimental nature of Reinforcement Learning and agent development.Agentic Threat Modeling: Partner with researchers to model threats specific to autonomous agents. Beyond standard AI risks, you will analyze risks unique to agents, such as goal misalignment, reward hacking, infinite looping, and insecure tool execution (e.g., an agent executing a command that exceeds safety limits).Secure Agent Architecture & Safety Boundaries: Design secure-by-default architectures for autonomous agents. Crucially, this involves defining deterministic safety guardrails that sit between the probabilistic AI model and the physical hardware controls. Ensure "Zero Trust" applies to the agent—it should only have the minimum permissions needed to adjust specific parameters.Secure Agent Tools & Memory: Architect security controls for the "tools" the agent uses (APIs to read sensors or change settings) and the agent's long-term memory. Ensure the agent cannot be manipulated into using a tool to perform unauthorized actions or "poisoned" via its memory context.MLSecOps for RL Pipelines: Secure the training and simulation pipelines used for Reinforcement Learning. Ensure the integrity of the simulation environments (Digital Twins) used to train agents, preventing attackers from influencing agent behavior during the training phase.Adversarial Testing & Red Teaming: Lead AI Red Teaming exercises focused on behavioral manipulation. Can you trick the agent into making a suboptimal decision? Can you manipulate the observations the agent receives?Incident Preparedness: Develop incident response playbooks tailored for autonomous systems, focusing on "Kill Switches" and rapid rollback capabilities in the event of rogue agent behavior.Cross-Functional Partnership: Build strong relationships with the Agentic AI researchers, SREs, and Data Scientists. Act as an enabler who helps them deploy powerful agents safely, rather than a blocker.Key QualificationsAgentic AI & RL Security: Proven understanding of the security risks associated with Reinforcement Learning, Autonomous Agents, or automated decision-making systems.AI Partnership: Demonstrated experience working embedded with AI system developers and researchers. You understand the difference between "probabilistic" (AI) and "deterministic" (Code) and how to secure the bridge between them.Core Experience: 5+ years of work experience in product security, application security, or a closely related security engineering role.Safety Engineering Mindset: You understand that in physical systems, "Availability" and "Safety" often outrank "Confidentiality." You are familiar with concepts like fail-safes and human-in-the-loop controls.Technical Depth:Strong programming experience, ideally with Python (essential for ML/AI ecosystems) or Go.Familiarity with agent frameworks (e.g., LangChain, AutoGPT) or RL libraries (e.g., Ray RLLib).Proven experience securing Cloud infrastructure (GCP) and Kubernetes.Deep understanding of Authentication & Authorization (specifically non-human identities/workload identity).Advanced MLOps: Direct, hands-on experience securing MLOps tooling (e.g., Kubeflow, MLflow) and deep understanding of securing complex data and model-training pipelines.Preferred Skills & ExperienceIndustrial / OT Context: Experience working with systems that interface with the physical world (IoT, Robotics, ICS/OT). Understanding of the "IT/OT convergence."Formal Verification for AI: Experience using mathematical methods to prove that an AI model or agent will not violate specific safety constraints.Sim-to-Real Security: Experience securing simulation environments (Digital Twins) and managing the security risks of transferring policies from simulation to the real world.Protocol Fuzzing: Ability to test industrial protocols (e.g., Modbus, BACnet) for robustness against automated or adversarial inputs.AI Governance: Familiarity with emerging standards like the NIST AI RMF or ISO 42001.Critical Systems: Experience securing "closed loops" or control systems where latency and reliability are critical.Certifications: Relevant advanced certifications, such as GICSP (Global Industrial Cyber Security Professional), ISA/IEC 62443 Cybersecurity Expert, NVIDIA Agentic AI, OSEP (Offensive Security Experienced Penetration Tester), CISSP, or OSCP.Our StackAI/ML: PyTorch, TensorFlow, Ray (RL), LangChain, Gemini/OpenAI/Anthropic models.Languages: Python, Go.Infrastructure: Docker, Kubernetes, Terraform.Cloud: GCP (GKE, PubSub, BigTable)Onboarding In your first 30 days — (Foundation and AI Landscape Familiarization)Understand the Mission: Deep dive into "Building AI for AI Factories." Understand the specific physical parameters (power, cooling, airflow) our agents are optimizing.Build Trust: Sit with the Agentic AI researchers to understand their workflow. How do they train agents? How do they simulate environments?Initial Review: Conduct a high-level review of the current "Safety Layer" that sits between the Agent and the control systems. In your first 60 days — (Threat Modeling & Guardrails):Agent Threat Model: Lead a detailed threat modeling session for a specific Agentic workflow. Focus on the Interface between the Agent and the Physical Hardware.Guardrail Implementation: Propose and begin implementing technical controls (guardrails) that enforce deterministic safety rules, ensuring the AI cannot exceed operational limits regardless of its intent.Secure the Tools: Review the security of the internal APIs (Tools) that the agents use to sense and act on the environment. In your first 90 days — (Strategy & Automation):Reference Architecture: Publish a "Secure Agent Reference Architecture" for future agent development.Driving Initiatives: Drive the implementation of the secure reference architectures and remediation of key findings from the threat modeling exercises.Demonstrable Impact: Showcase measurable improvements in the security of the AI/ML pipeline (e.g., implementation of runtime monitoring for anomalous model behavior, reduction of AI-specific vulnerabilities).Strategic Contributions: Establish yourself as the key security partner and expert for the Agentic AI Department.General Interview Process All of our interviews are held via Google Meet, and an active camera connection is required.Meeting with People Operations team member (30 minutes)Meeting with Hiring Manager (30 minutes)Technical Interview with our Senior Product Security Engineer (60 minutes)Meeting with Agentic AI team member (45 minutes)Culture fit interview with Phaidra's co-founders (30 minutes)Base Salary US Residents:Tier 1 (Largest highest-cost metros): 146,200 USD - 199,600 USDTier 2 (Other major metros): 138,640 USD - 189,370 USDTier 3 (Mid-sized metro areas): 131,080 USD - 179,140 USDTier 4 (All other locations): 123,520 USD - 168,910 USD UK Residents:Tier 1 (London): 95,200 GBP - 142,000 GBPTier 2 (Manchester, Birmingham, Edinburgh, Bristol): 89,600 GBP - 134,400 GBPTier 3 (Other areas): 84,000 GPB - 126,000 GBP In addition to base salary, this position is eligible for equity. Final salary will be determined based on several factors, including a candidate's qualifications, skills, competencies, experience, expertise, education and location. In some cases, final compensation may fall outside the posted range. Salary ranges are regularly reviewed and may be adjusted in response to market trends. Benefits & PerksFast-paced, team-oriented environment where your work directly shapes the company's direction.We are a 100% remote company. Competitive compensation & meaningful equity.Outsized responsibilities & professional development.Training is foundational; functional, customer immersion, and development training.Medical, dental, and vision insurance (exact benefits vary by region).Unlimited paid time off, with a required minimum of 20 days per year.Paid parental leave (exact benefits vary by region).Flexible stipends to support your workspace, well-being, and continued professional development.Company MacBook. Please note: Not all of Phaidra's benefits and perks listed above apply to temporary employees such as interns.On being Remote We take a thoughtful and intentional approach to remote collaboration. Inspired by pioneers like GitLab, we embrace proven best practices to foster an exceptional remote work environment. Our culture is documentation-first, and we prioritize asynchronous communication to support focus and flexibility across time zones. While we value independence, we stay closely connected through tools like Slack and video conferencing. Weekly all-hands meetings help us align and build strong relationships, and we regularly host virtual team-building activities and social events to maintain a sense of camaraderie.Equal Opportunity Employment Phaidra is an Equal Opportunity Employer; employment with Phaidra is governed on the basis of merit, competence, and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status. We welcome diversity and strive to maintain an inclusive environment for all employees. If you need assistance with completing the application process, please contact us at Notice Phaidra participates in E-Verify, an employment authorization database provided through the U.S. Department of Homeland Security (DHS) and Social Security Administration (SSA). As required by law, we will provide the SSA and, if necessary, the DHS, with information from each new employee's Form I-9 to confirm work authorization for those residing in the United States. Additional information about E-Verify can be found here. #LI-Remote To be considered for any position at Phaidra, you must submit an online application. This role will remain open until it is filled. Phaidra only hires individuals who are legally authorized to work in the specified location(s) above. We do not provide employment sponsorship. Candidates requiring visa sponsorship, either now or in the future, are not eligible for hire. WE DO NOT ACCEPT APPLICATIONS FROM RECRUITERS.

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 Senior Manager, Commercial Analytics & Data ScienceHow you’ll make an impact: • You will build machine learning models to answer key business questions impacting strategy and marketing spend allocation, • You will perform feature engineering and contribute to our feature store, • You will lead dashboard development and lead development of enhanced visualization toolsResponsibilities: What you’ll do:, • Build advanced machine learning models to inform marketing tactics (examples: adaptive clustering, reinforcement learning, regression modeling, price elasticity modeling etc.), • Execute sophisticated quantitative analyses and descriptive modeling to answer key business questions to shape business strategy., • Use enhanced python based graphical visualizations to deliver key insights to leadership., • Research and implement novel modeling techniques to solve complex business problems., • Develop analytics databases & lead development and maintenance of automated dashboards for AB experiment results., • Develop complex SQL queries combining data from a wide variety of sources in preparation of feature engineering or to perform analysis of business questions., • Measure incrementality of paid media campaigns using matched market testing.Requirements: What you’ll need:, • Bachelor’s or Master's degree in data science, computer science, statistics, engineering, or related quantitative field., • Strong prior experience in data science, business & statistical analytics., • 7+ years of experience in related field., • Strong background in SQL & Python, R is a plus., • Experience in machine learning algorithms & libraries. Examples: CausalML/EconML, TensorFlow, PyTorch, Keras, sk-learn, seaborn, LSTM, RNN., • Experience in visualization tools. Examples: Databrick AI/BI, Rshiny, Dash, Tableau., • Familiarity with Databricks platform is a plus., • Willingness to take initiative and to follow through on projects., • Excellent time management skills with the ability to prioritize and multi-task, and work under shifting deadlines in a fast-paced environment., • Must have legal right to work in the U.S.Compensation:, • $100 to $105/hr. (W2)Job req# 1654-1

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 to pursue greater human understanding, pioneering 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 seventeen 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 Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Applied Generative AI. 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. The Applied Generative AI course provides students with a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation. Responsibilities * Attend all 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. 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 an area related to Machine Learning, Computer Science, Applied Mathematics, or related field. * 3+ years of related applied professional experience. Preferred Skills & Experience * Programming experience in Python and experience with major deep learning frameworks such as PyTorch or TensorFlow. * Knowledge of deep learning architectures, such as CNNs, VAEs, GANs, and RNNs. * Experience with deploying code on cloud platforms such as AWS, GCP, or Azure. * Knowledge of Mathematics and Probability concepts used in machine learning, including * Optimization, Gradient Descent, Conditional Probability, Bayes Theorem, and Normal Distribution. 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 DescriptionFounding AI/ML Engineer Location: New York, NY or San Francisco, CA (Hybrid – 3 days onsite) Employment Type: Full-Time Compensation: $125,000 – $200,000 base + 0.3% – 1% equity + bonus About the Company Our client is building advanced AI systems that help law enforcement agencies search digital evidence and accelerate investigations. Their platform processes large-scale video, audio, and text datasets to surface investigative leads quickly and accurately. Backed by leading venture investors and already serving live, paying customers, the company is entering a high-growth phase. The founding engineering team includes experienced builders of national-scale systems, and this role will be instrumental in shaping the technical foundation of the platform. The Opportunity This is a founding-level engineering role with significant ownership and impact. You will design, build, and scale the core backend infrastructure and applied machine learning systems that power the platforms intelligence layer. You will work across infrastructure and model deployment, building secure, distributed systems in highly sensitive environments. Key Responsibilities • Design and scale backend infrastructure for AI-driven systems, • Build and deploy applied ML systems in production, • Architect retrieval pipelines and integrate LLM and VLM technologies, • Process and manage high-volume multimodal datasets (video, audio, text), • Develop secure distributed systems that meet strict compliance standards, • Own end-to-end deployment from architecture through productionRequired Qualifications, • 3+ years of engineering experience (4–6+ preferred), • 2+ years of hands-on applied ML experience, • Strong backend development skills in Python, • Experience with ML Ops frameworks such as FastAPI, LangChain, PyTorch, • Proven track record deploying production-grade ML systems, • U.S. work authorization (no visa sponsorship available), • Willingness to undergo FBI or CJIS background clearancePreferred Experience, • Built secure distributed systems using Python, Go, or TypeScript, • Experience across both infrastructure and model-level implementation, • Worked on real-time or high-throughput data systems, • Competitive base salary ($125K–$200K), • Meaningful founding-level equity (0.3%–1%), • Performance bonuses, • 3% 401(k) contribution (no employee match required), • Full health and dental coverage, • Unlimited PTO, • Free lunches and dinners, • Gym reimbursement, • Sponsored FBI/CJIS clearance, • Well-funded, fast-growing team with strong technical leadership

Job Description The Role Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. As a Senior Computational Biologist, you'll work alongside members of our research team and our founders to develop AI systems capable of complex biological reasoning across multiple scales. * You will develop machine learning methods to extend our predictive and generative platform * You will design and execute computational pipelines to validate and prioritized de novo generated molecules using state of the art tools * You will use your deep understanding of biology to design novel therapeutics for hard-to-target proteins with our generative models * You will analyze and integrate large-scale biological datasets * Your work will directly impact the development of our biologically-aware AI platform, transforming the landscape of medicine Make a real tangible impact on millions of lives by pushing the boundaries of AI in biology. Who We're Looking For * You have a PhD in a biological field and strong programming skills in Python * You have experience with computational biology tools such as structure prediction, molecular docking and virtual screening * You have experience working with Protein or Chemical Language Models * You like to work collaboratively in a fast-paced startup environment * You are passionate about using data science to unlock the secrets of biology * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty * You have excellent communication skills and can clearly articulate complex technical concepts Bonus Points * You have hands-on experience building AI/ML using PyTorch and Lightning * You have experience with cloud computing platforms like AWS * You have hands-on biology laboratory experience * You have contributed to peer-reviewed publications in computational biology * You have knowledge of machine learning techniques applied to biological data Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $150K - $250K

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 a full time Research Scientist, Artificial Intelligence (PhD) to join our growing team of researchers & engineers. If you're passionate about shaping the future of brain-computer interfaces and excited by the potential of deep learning in neurotechnology, we want to hear from you! Responsibilities: • Design, prototype, and optimize state-of-the-art AI systems for neural decoding, including diffusion models, graph neural networks, contrastive/self-supervised frameworks, and transformer-based sequence models., • Conduct foundational research on neural time-series representation learning: build architectures that extract latent dynamics from EEG, EMG, or related biosignals., • Develop high-fidelity simulation environments for testing decoding algorithms, incorporating stochastic signal noise and realistic biophysical constraints., • Scale model training across multi-GPU and multi-node clusters using PyTorch Distributed, DeepSpeed, or JAX/Flax; profile and tune system performance for sub-10 ms inference latency., • Build and maintain end-to-end research pipelines for large-scale signal datasets, including preprocessing, artifact rejection, and multimodal fusion with video, audio, and IMU data., • Collaborate with neuroscientists and hardware engineers to integrate learned models into real-time BCI control loops and embedded systems., • Contribute to core ML infrastructure: experiment tracking, model versioning, dataset lineage, and reproducibility standards., • PhD or equivalent deep technical expertise in Machine Learning, Artificial Intelligence, Computer Science, Computational Neuroscience, or related fields., • Strong command of PyTorch or JAX, with experience implementing custom training loops, loss functions, and model architectures., • Proven ability to conduct end-to-end research, from conceptual design to reproducible experiments and evaluation., • Strong mathematical foundations in linear algebra, probability, optimization, and information theory., • Experience working with high-dimensional time-series or sensory data (EEG, speech, video, motion capture, etc.)., • Skilled in Python, NumPy, Pandas, and scientific computing workflows; experience with CUDA or low-level GPU debugging is highly valued., • Deep familiarity with neural signal modeling, neural decoding, or biosignal preprocessing (EEG/MEG/ECoG/EMG)., • Experience designing self-supervised or generative models (diffusion, VAEs, contrastive, masked modeling) for noisy, non-stationary data., • Background in reinforcement learning, optimal control, or human-in-the-loop systems, especially in continuous domains., • Publications or preprints in top venues (NeurIPS, ICML, ICLR, CVPR, EMBC, Nature Neuro)., • Familiarity with distributed training, mixed-precision, multi-GPU orchestration, and cloud ML infrastructure (AWS/GCP/Azure)., • Contributions to open-source ML frameworks or custom CUDA kernels., • Understanding of neural signal acquisition hardware, embedded inference, or edge ML deployment. 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. Expected Compensation: The base salary for this role is anticipated to fall within the following range. Actual compensation will depend on your experience, technical expertise, and relevant education or training. In addition to base pay, Synaptrix offers equity to all full-time employees, reflecting our commitment to shared success and long-term company growth. Base Salary Range: $85,000 - $150,000 USD What We Offer: • An opportunity to change the world and work with some of the smartest and most talented experts from different fields, • Growth potential; we rapidly advance team members who have an outsized impact, • Paid holidays, unlimited PTO

Job DescriptionCompany Description At Fun, we believe a tokenized future is a beneficial inevitability, granting financial emancipation to everyone with an internet connection. For a blockchain-first global economy to exist, value exchange must become intuitive, secure, and seamless. Enter Checkout — the highest converting payment solution in web3. By integrating Checkout, dApps enable users to complete any on-chain action using crypto from a wallet, centralized exchange, or on-ramped fiat from a card or bank account. With access to market-leading routing and their asset portfolio at the point of sale, users are faster, stickier, and more engaged. For dApps, Checkout scales their user acquisition potential without launching new chains or integrating multiple third party providers. We built Checkout because we envision a world where anyone, anywhere, can purchase anything with any asset. If that sounds like a vision you can get behind, we want to hear from you. Role Overview We’re looking for a Data Scientist to supercharge our data-driven strategy and ensure we’re building the right things at the right time. You’ll be embedded in the heart of our product and engineering teams, shaping insights that guide strategy, uncover user behavior, and optimize execution across Fun. This role is perfect for someone who thrives in fast-paced, ownership-driven environments, loves solving open-ended problems, and is excited about the potential of blockchain data.Responsibilities • Design and build scalable data models to analyze transaction flows and user behavior, • Support the optimization of data transformations, pipelines, and workflows, • Work directly with the CFO to provide insights on the business’ performance, • Maintain data quality, observability, and reproducibility across analytical systems, • Partner with engineers and product teams to deliver actionable, production-grade insights, • Run experiments, apply causal inference, and drive evidence-based product decisions, • Translate complex data into clear stories for both technical and non-technical stakeholdersRequirements, • Proficiency in Python and SQL (5+ years), • Strong background in statistical analysis, experimentation, and causal inference, • Familiar with analyzing end-user behavior for optimization (A/B testing, conversion rates, etc.), • Skilled in modern data platforms (Redshift, Snowflake, Databricks, etc.) and orchestration/transformation tools (dbt or similar), • Deep curiosity about crypto, DeFi, on-chain data, and Web3 infrastructureNice To Have, • Experience analyzing large-scale transaction or financial datasets, • Hands-on experience with ML/AI libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow), • Familiarity with market dynamics (spreads, slippage, liquidity, etc.), • A track record of thriving in ownership-heavy, fast-moving environments

Job DescriptionCompany Description For More Open Positions Visit us at: Our Mission WOONGJIN, Inc. is a rapidly growing team who provides a range of unique, exceptional, and enhanced services to our clients. We have a strong moral code that includes the service of goodness without expectations of reward. We are motivated by the sense of responsibility and servant leadership. Benefits • Medical Insurance, • Vision Insurance, • Dental Insurance, • 401(k), • Paid Sick hoursJob Description, • Design and develop algorithms for generative models using deep learning techniques, • Design and build LLM-powered applications for internal and/or customer-facing use cases, • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems, • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration, • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate, • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability, • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies, • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices, • Build monitoring, observability, and feedback loops for model and application performance in production, • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems, • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities, • Mentor other engineers and contribute to architecture, technical direction, and engineering best practicesQualifications Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience, • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production, • Strong programming skills in Python and experience with backend/API development, • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design, • Experience in optimizing RAG pipelines using both structured and unstructured data, • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent, • Experience in generative AI techniques such as GANs, and VAEs, • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search, • Experience with cloud platforms such as AWS, GCP, or Azure, • Experience with Docker, Kubernetes, CI/CD, and production deployment practices, • Strong understanding of software architecture, scalability, reliability, and distributed systems, • Experience building evaluation, testing, and monitoring for AI systems, • Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications • Experience fine-tuning or adapting open-source LLMs, • Advanced knowledge of natural language processing for text generation tasks, • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks, • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar, • Experience building multi-agent systems or advanced orchestration workflows, • Experience with AI safety, guardrails, red-teaming, privacy, and governance, • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems, • Experience in customer-facing or enterprise SaaS products, • Experience in semiconductor/manufacturing, retail and e-commerce sectors What Success Looks Like • Deliver production-ready GenAI features that improve user experience and business outcomes, • Build reliable and scalable AI systems with strong quality, latency, and cost performance, • Establish best practices for evaluation, observability, and responsible AI development, • Help define the company’s long-term Generative AI architecture and roadma Additional Information All your information will be kept confidential according to EEO guidelines. * NO C2C *

Job DescriptionAbout Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on . About The Job: Technical Lead, Applied AI Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases. You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings. As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision. What you will do - Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions.- Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries.- Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders.- Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives.- Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment.- Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle. About you- You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field.- You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions.- You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation.- You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale.- You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus.- You have strong software engineering skills, including API design, backend/full-stack development, and system architecture.- You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers.- You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent. Ideally, you have:- Contributed to open-source projects, particularly in the LLM or AI space.- Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption.- A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities. Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!What we offer • \uD83D\uDCB0 Competitive salary and equity., • \uD83D\uDE91 Healthcare: Medical/Dental/Vision covered for you and your family., • \uD83D\uDC74\uD83C\uDFFB Pension : 401K (6% matching), • \uD83C\uDFDD️ PTO : 18 days, • \uD83D\uDE97 Transportation: Reimburse office parking charges, or $120/month for public transport, • \uD83C\uDFC0 Sport: $120/month reimbursement for gym membership, • \uD83E\uDD55 Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger), • \uD83C\uDF0E Visa sponsorship, • \uD83E\uDD1D Coaching: we offer BetterUp coaching on a voluntary basis By applying, you agree to our Applicant Privacy Policy.

Job Description Position: AI/MLEngineer Location: NYCNY/Atlanta GA (In-Person Interview) Duration: 12 Months Need Only Locals to NY and GA Face to Face Interview - W2 Contract only Skills and Responsibilities: Build end-to-end AI/ML systems,including scalable ML pipelines, production-grade models, and full MLOpsinfrastructure for training, deployment, monitoring, andautomation. Develop solutions using Python,Docker, Kubernetes, Bash, PowerShell, SQL/NoSQL/vector databases, and cloudplatforms such as AWS, Azure, GCP, or OCI. Skilled in Apache Kafkafor event-driven systems Design and deploy ML models across domains like NLP/LLMs (BERT, GPT,RAG, fine-tuning), time-series forecasting, recommendersystems, and distributed training on multi-GPU or multi-nodesetups. Use MLOps and workflow tools including MLflow,Weights & Biases, Kubeflow, Airflow, and cloud AI services(Azure AI, AWS SageMaker/Bedrock, GCP Vertex AI, OCI AI). Build internal tools, CLI-first utilities, and efficient MLworkflows for high-scale production environments. Optional experience includes CI/CD (Azure DevOps, GitHubActions, Jenkins), computer vision (PyTorch/TensorFlow), Go/Rust,feature stores, model optimization, edge deployment, A/B testing, open-source ML,and real-time streaming (Kafka, Kinesis).

Job DescriptionAbout Quizlet: At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. We’re a $1B+ learning platform used by two-thirds of U.S. high school students and half of college students, powering over 1 billion learning interactions each week. We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of LearningJoin us to design and deliver AI-powered learning tools that scale across the world and unlock human potential. About the Team: The Personalization & Recommendations team at Quizlet is building personalized learning experiences that help millions of learners study more effectively. We are looking for Machine Learning Engineers ranging from the Senior to Staff as well as Sr. Staff levels (note: leveling decisions made through the interview process). You’ll bring strong expertise in modern recommender systems — from deep learning–based retrieval and embeddings to multi-stage ranking and evaluation — and contribute to the evolution of Quizlet’s personalization capabilities. You’ll work at the intersection of machine learning, product, and scalable systems, ensuring our recommendations are performant, responsible, and aligned with learner outcomes, privacy, and fairness. We’re happy to share that this is an onsite position. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe this work environment enhances efficiency, fosters collaboration, and supports growth for both employees and the organization. In this role, you will: • Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals, and content features., • Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization., • Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training-serving consistency, observability, and robust monitoring., • Partner with Product and Data Science to translate learner objectives such as engagement, retention, and mastery into measurable modeling goals and experiment designs., • Advance evaluation methodologies, contributing to offline metric design such as NDCG, CTR, AUC, and calibration, and supporting rigorous A/B testing to measure learner and business impact., • Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments., • Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem., • Mentor engineers, supporting technical growth, experimentation rigor, and responsible ML practices., • Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture., • Depending on level, contribute to broader technical strategy, guide architectural decisions, and influence personalization direction across teams and product surfaces.What you bring to the table:, • Minimum 5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems., • Demonstrated impact improving key metrics such as CTR, retention, engagement, or other learner-facing outcomes through recommender or search systems in production., • Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices, including model registries, feature stores, monitoring, and drift detection., • Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, MMoE, or similar approaches, and the ability to apply them to real-world problems., • Experience with large-scale embedding models and vector search systems, including FAISS, ScaNN, or similar technologies., • Proficiency in experiment design and evaluation, connecting offline metrics such as AUC, NDCG, and calibration with online A/B test outcomes to drive product decisions., • Clear, effective communication, with the ability to collaborate well with product managers, data scientists, engineers, and cross-functional partners., • A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability., • Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals.Additional strengths for Senior Staff candidates:, • Experience shaping technical strategy across teams or disciplines, balancing long-term architectural vision with near-term product and business priorities., • Demonstrated leadership through influence, including aligning stakeholders, guiding teams through ambiguity, and driving accountability for outcomes., • Ability to communicate complex technical trade-offs clearly to senior leadership and cross-functional audiences., • Experience mentoring senior engineers or applied scientists and helping raise the technical bar across an organization., • Proven ability to lead large, ambiguous initiatives and influence platform, product, and modeling direction at scale.Bonus points if you have:, • Publications or open-source contributions in RecSys, search, or ranking., • Familiarity with reinforcement learning for recommendations or contextual bandits., • Experience with hybrid RecSys systems blending collaborative filtering, content understanding, and LLM-based reasoning., • Prior work in consumer or EdTech applications with personalization at scale.Compensation, Benefits & Perks:, • Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a base salary of $175,000 to $330,000 depending on location, level (Senior, Staff, or Senior Staff), and experience, as well as company stock options, • Collaborate with your manager and team to create a healthy work-life balance, • 20 vacation days that we expect you to take!, • Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice), • Employer-sponsored 401k plan with company match, • Access to LinkedIn Learning and other resources to support professional growth, • Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits We strive to make everyone feel comfortable and welcome!We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership. We provide a transparent setting that gives a comprehensive view of who we are! In Closing: At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.” Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion. As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us! To All Recruiters and Placement Agencies: At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.#LI-onsite We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Location: Cambridge, MA (Eastern Time / UTC -4) Relocation package available Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers. We are seeking a Staff / Principal ML Ops Engineer to lead the design, implementation, and scaling of the companys ML infrastructure and production AI systems. This is a high-impact, architecture-defining role where youll work across the entire model lifecycletraining, evaluation, deployment, observability, and continuous optimization. You will partner closely with AI researchers, GPU systems engineers, backend teams, and product stakeholders to ensure the companys large-scale AI systems are robust, efficient, automated, and production-grade. This role is ideal for someone who has already built and owned ML platforms at scale and can drive strategy as well as hands-on execution. What Youll Do • Architect, build, and scale the end-to-end ML Ops pipeline, including training, fine-tuning, evaluation, rollout, and monitoring., • Design reliable infrastructure for model deployment, versioning, reproducibility, and orchestration across cloud and on-prem GPU clusters., • Optimize compute usage across distributed systems (Kubernetes, autoscaling, caching, GPU allocation, checkpointing workflows)., • Lead the implementation of observability for ML systems (monitor drift, performance, throughput, reliability, cost)., • Build automated workflows for dataset curation, labeling, feature pipelines, evaluation, and CI/CD for ML models., • Collaborate with researchers to productionize models and accelerate training/inference pipelines., • Establish ML Ops best practices, internal standards, and cross-team tooling., • Deep hands-on experience designing and operating production ML systems at scale (Staff/Principal-level expected)., • Strong background in ML Ops, distributed systems, and cloud infrastructure (AWS, GCP, or Azure)., • Proficiency with Python and familiarity with TypeScript or Go for platform integration., • Expertise in ML frameworks: PyTorch, Transformers, vLLM, Llama-factory, Megatron-LM, CUDA / GPU acceleration (practical understanding), • Strong experience with containerization and orchestration (Docker, Kubernetes, Helm, autoscaling)., • Deep understanding of ML lifecycle workflows: training, fine-tuning, evaluation, inference, model registries., • Experience deploying and operating LLMs and generative models in production at enterprise scale., • Familiarity with DevOps, CI/CD, automated deployment pipelines, and infrastructure-as-code., • Experience optimizing GPU clusters, scheduling, and distributed training frameworks., • Prior startup experience or comfort operating with ambiguity and high ownership., • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions., • Customer impact: Deploy AI solutions powering Fortune 500 clients., • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave)., • Funding & growth: Oversubscribed seed round, next funding in 2026., • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale., • Culture & autonomy: Own critical systems while collaborating with world-class engineers., • Competitive salary & equity options, • Sign-on bonus, • Health, Dental, and Vision

Job DescriptionCoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do The Field Engineering team at Weights & Biases plays a vital role in ensuring customer success and adoption of our platform. As part of this team, we partner with Sales, Support, Product, and Engineering to lead technical success after the sales process. We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs). About the Role We're hiring an AI Solutions Engineer, Post-Sales to help customers solve real-world problems by enabling them to implement and scale ML pipelines and agentic workflows using Weights & Biases. In this role, you'll collaborate with engineering teams to ensure smooth onboarding and adoption, act as a trusted advisor on best practices, and represent the voice of the customer internally. You will partner directly with leading AI teams to optimize workflows, share technical expertise, and influence our product roadmap based on real-world customer feedback. This is an ideal opportunity for ML practitioners who are customer-focused and eager to work with top AI companies globally. Who You Are • 3–5 years of relevant experience in a similar role, • Strong programming proficiency in Python, • Hands-on experience enabling production-grade ML systems, with a focus on training and inference pipelines, experiment tracking, deployment patterns, and observability using deep learning frameworks (TensorFlow/Keras, PyTorch/PyTorch Lightning) and MLOps tooling (e.g. Airflow, Kubeflow, Ray, TensorRT)., • Familiarity with cloud platforms (AWS, GCP, Azure), • Experience with GenAI/LLMs and related tools (e.g. LangChain/LangGraph, HuggingFace Transformers, Pinecone, Weaviate), • Strong experience with Linux/Unix, • Excellent communication and presentation skills, both written and verbal, • Ability to break down and solve complex problems through customer consultation and execution, • Background in robotics, • TypeScript experience, • Proficiency with Fastai, scikit-learn, XGBoost, or LightGBM, • Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes, • You love collaborating with top AI teams to solve real-world ML and GenAI challenges, • You're curious about how to optimize AI workflows at scale, • Be Curious at Your Core, • Act Like an Owner, • Empower Employees, • Deliver Best-in-Class Client Experiences The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs, including: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration. California Consumer Privacy Act - California applicants only CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Job Title: Machine Learning Engineering Director Qualifications: • Hold a Bachelor's degree in a technical field (e.g., computer science, machine learning, mathematics, physics, statistics, econometrics), or equivalent hands-on experience., • Demonstrate coding proficiency in at least one programming language, with a strong preference for Python., • Possess a strong foundation in mathematics, statistics, and machine learning concepts, enabling the development, training, and evaluation of production models and facilitating the comprehension of research papers., • Showcase exceptional communication skills, facilitating the effective conveyance of technical ideas and fostering productive collaborations with business partners., • Exhibit an entrepreneurial mindset and a deep passion for unlocking the potential of Large Language Models (LLMs) and classical machine learning techniques to drive a multi-billion dollar business., • Provide evidence of successful management experience, having effectively led teams of 1-2 machine learning engineers or scientists., • Proficiency in building RESTful APIs, ideally using Flask, FastAPI, or other Python frameworks., • Experience in constructing data pipelines that underpin Machine Learning model development., • Familiarity with Python libraries for machine learning, data manipulation, and mathematics, such as PyTorch, numpy, and pandas.

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 DescriptionJob Description Summary – AI Optimization Engineer (Onsite, Jersey City, NJ) We are seeking an experienced AI Optimization Engineer to support large-scale AI/ML and Generative AI workloads for an enterprise environment. This role focuses on optimizing, deploying, and managing machine learning and large language models (LLMs) on GPU-accelerated HPC infrastructure. The ideal candidate will have strong experience in Python-based machine learning, deep learning frameworks, model optimization techniques, and scalable AI infrastructure. The engineer will work closely with AI, infrastructure, and DevOps teams to design efficient model training and inference pipelines, implement SLURM-based workload orchestration, and deploy containerized ML solutions in production environments. Responsibilities include optimizing model performance using techniques such as pruning, quantization, and knowledge distillation, managing inference workflows using Triton Inference Server, and monitoring system performance using Prometheus and Grafana. This role requires hands-on experience with HPC environments, GPU clusters, containerization technologies, and Linux system administration, along with strong knowledge of machine learning algorithms, deep learning architectures, and modern AI development tools. Experience with cloud platforms, vector embedding, and enterprise-scale AI deployments is highly preferred. Core Responsibilities * Design and optimize AI/ML workloads on GPU-based HPC clusters. * Deploy and manage large language models (LLMs) in scalable production environments. * Implement model optimization techniques including pruning, quantization, and knowledge distillation. * Develop and manage automated job scheduling using SLURM with REST and Flask APIs. * Deploy ML models using containerized microservices architectures. * Monitor system performance using Prometheus and Grafana. * Optimize inference pipelines using Triton Inference Server and TRTLLM. * Conduct exploratory data analysis and model performance evaluation. * Collaborate with infrastructure and ML teams to improve scalability and efficiency. Skills Required The AI Optimization Engineer must have strong experience in Python-based machine learning and deep learning, including NumPy, scikit-learn, TensorFlow, PyTorch, and Keras, with hands-on knowledge of supervised and unsupervised learning, neural networks, transformer-based models, NLP, CNNs, and Generative AI concepts. The role requires expertise in AI infrastructure and optimization, including HPC environments, GPU clusters, SLURM workload management, Triton Inference Server, TRTLLM, and model optimization techniques such as pruning, quantization, and distillation for scalable LLM deployment. Candidates should also have experience with DevOps and deployment tools such as Docker, Kubernetes, MLFlow, Terraform, Jenkins, GitHub, and HuggingFace, along with strong skills in performance monitoring using Prometheus and Grafana. Additional requirements include Flask API development, Linux administration (RHEL/CentOS), container runtimes like Enroot, Pyxis, and Podman, and experience with data analysis and visualization tools such as Plotly, Seaborn, and Matplotlib.

Job DescriptionSchmidt Sciences is a nonprofit organization founded in 2024 by Eric and Wendy Schmidt that works to accelerate scientific knowledge and breakthroughs with the most promising, advanced tools to support a thriving planet. The organization prioritizes research in areas poised for impact including AI and advanced computing, astrophysics, biosciences, climate, and space—as well as supporting researchers in a variety of disciplines through its science systems program. About the AI & Advanced Computing Institute (“AI Institute”) The AI Institute at Schmidt Sciences is a grantmaking and research group that views AI as a transformative force for scientific discovery and societal progress. Over the next decade, we aim to support key researchers who are working to make AI systems competent, trustworthy, reliable, and able to effectively partner with human scientists on the next generation of discovery. We will also make selected distinctive investments in beneficial AI areas where philanthropy has a unique advantage. By supporting enabling infrastructure, foundational research, and targeted programs in science disciplines, the AI and Advanced Computing Institute will create the conditions for AI-enabled discovery to achieve its promise. The AI Institute currently has three focus areas: AI for Science – using AI to improve how scientists generate hypotheses, conduct experiments, analyze data, and produce new knowledge – and do this in a way that specifically accelerates the discovery process. Exploratory programs include post-transistor hardware for AI and AI for scientific simulation. Science of AI – understanding and controlling AI systems to mitigate and manage potential risks from advanced AI. Improve AI reliability and performance in areas of limited commercial interest. Existing programs include AI2050 and Science of Trustworthy AI. Exploratory programs include AI interpretability and evolution of multi-agent communication. Beneficial AI – providing scientific foundations and datasets for understanding the larger human impacts of AI. This includes selected high-impact grantmaking, such as our programs to use AI to accelerate humanities research (Humanities and AI Virtual Institute), and to quantify the impact of AI on the labor market (AI@Work). The Role Reporting to the Director of the AI Institute at Schmidt Sciences, the Senior Program Scientist will provide technical leadership and people management across the AI Institute, as well as contribute to the overall strategy of Schmidt Sciences. This is not a traditional research or industry role; rather, impact in this role is achieved by enabling high-quality academic and industry progress through funding, development of scientific instruments and other supports, convening, ecosystem building, and thought leadership. Success for this role is the ability to position the AI Institute as the premier funder of AI scientific research globally, with a reputation for selecting the hardest technical challenges and using philanthropy to significantly advance solutions to them. In short, the ambition here is to influence the next decade of scientific discovery. Key Responsibilities for this role include the following:Strategic Leadership • Support the Institute lead in the design, evolution, and execution of the AI Institute’s current and future strategic, scientific, and technical direction., • Co-design multi-year research agendas., • Identify areas of AI where early philanthropy entry can provide significant advancement., • Contribute to the overall scientific priorities in the AI and advanced computing portfolio and set future directions for engagementTechnical Evaluation and Program Development, • Provide technical advice to the existing programs and major awards of the AI Institute., • As needed, work with team members to develop new programs. Note: current program explorations include AI interpretability, evolution of communication of multi-agent systems, post-transistor AI hardware, and AI-enabled simulation of scientific processes., • Support existing AI Institute programs by providing networking assistance, scientific expertise, and mentorship, as necessary, and by working closely and collaboratively with the teams responsible for delivery. Contribute to the team’s assessment of expressions of interest and research proposals. Team Management, • Manage 3-5 program scientists and visiting scientists to help them continue to grow their scientific discernment and grantmaking skills., • Contribute to the improvement of the AI team’s operations, including our grantmaking, budgeting, events & convening, and other processes.External Engagement and Ecosystem Building, • Act as a conduit for bringing in innovative ideas and perspectives from the AI community, actively engaging with stakeholders to identify emerging trends and opportunities for collaboration.Schmidt Sciences Support, • Serve as an expert advisor at Schmidt Sciences on topics in AI and advanced computing, with a focus on AI and humanities., • Work with other members of the Schmidt Sciences team to drive organizational priorities and model our values., • Identify potential partners for Schmidt Sciences, including universities, labs, other research facilities, and philanthropic and government organizations., • Participate in relevant industry or academic conferences and events, representing Schmidt Sciences’ presence on AI and advanced computing issues.Required Knowledge, Skills, and Abilities, • Advanced degree (e.g., PhD), from an accredited institution, with a focus on artificial intelligence, • 10+ years of academic and industry experience in artificial intelligence, • Deep understanding of modern machine learning, including deep learning, probabilistic modeling, generative models, reinforcement learning, and large-scale representation learning, • Experience leading teams and managing technical staff, • Hands-on experience designing, training, and evaluating state-of-the-art models (e.g., foundation models, multimodal systems, agentic AI, simulation-based models), • Demonstrated track record of scientific accomplishments, evidenced by peer-reviewed publications, patents, successful grant applications, or contributions to innovative industry projects, • Ability to critically evaluate scientific, technical, and other AI-related claims in grant proposals and other technical opportunities and emerging methods, • Deep relationships in the AI community and experience working with AI-focused institutions, • Experience producing technical writing for expert and general audiences, • Demonstrated ability to collaborate and a record of impact in high-intensity, team-based environments, • Sense of urgency in driving work to completion, • The highest integrity and ability to maintain confidentiality, • Be able to travel within the U.S. and internationally on a regular basis as neededPreferred Knowledge, Skills, and Abilities, • Hands-on AI Experience: Experience building prototypes, benchmarks, or proof-of-concept systems to test scientific hypotheses or assess research investments. Strong fluency in ML engineering tools and best practices (Python, PyTorch/JAX/TF, data pipelines, MLOps, evaluation frameworks). Experience evaluating the scalability, data requirements, compute needs, and infrastructure implications of ambitious AI projects., • Expertise in Specific Focus Areas for the AI Institute, Including: AI model evaluation and red-teaming for scientific reliability, Mechanistic interpretability or auditing methods, Multi-agent systems and emergent behavior, AI-accelerated simulation frameworks, • AI x Science: Familiarity with how AI is used across scientific disciplines (biology, chemistry, physics, climate science, neuroscience, etc.). Expertise in at least one scientific domain where AI is meaningfully accelerating research (e.g., protein structure prediction, generative chemistry, computational biology, materials discovery, climate modeling). Ability to work and translate technical concepts across multiple scientific disciplines

Job Description🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 💻 Role * Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent behaviors across users, payments, and marketplace interactions. * Lead the end-to-end architecture of fraud detection, prevention, and intervention systems — balancing platform security with a seamless user experience. * Build intelligent user graphs to model behavioral patterns, collusion networks, and account connectivity. * Develop scalable data pipelines and real-time inference systems supporting high-volume, low-latency ML workloads. * Conduct deep behavioral and adversarial data analysis to uncover fraud trends and continuously improve detection accuracy. * Partner cross-functionally with Trust & Safety, Payments, and Infrastructure teams to develop features, labels, and model evaluation pipelines. * Implement model monitoring and drift detection systems to ensure reliability and responsiveness. * Contribute to fraud risk orchestration, combining rules, models, and heuristics for decision automation. * Define and track key metrics and dashboards for fraud detection effectiveness (e.g., precision, recall, false-positive rate, latency). * Stay ahead of emerging fraud tactics and continuously translate insights into adaptive, production-ready systems. We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our SF, NYC, LA OR SEA hubs. 👋 You People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it. * Bachelor’s degree in Computer Science, a related field, or equivalent work experience. * 2–6 years of experience in machine learning or software engineering, ideally in risk, fraud, or trust & safety domains. * Strong proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, LightGBM). * Solid backend development skills and experience deploying ML models to production (batch or real-time). * Experience in data analysis and ETL (SQL, Spark, DBT) for data pipeline building. * Familiarity with fraud detection techniques such as chargeback prediction, anomaly detection, or graph-based modeling. * Experience with data orchestration frameworks (Dagster, Kubeflow) and feature store design. * Ability to translate business risk into measurable ML solutions and collaborate across diverse 💰Compensation For US-based applicants: $245,000 - $345,000/year + benefits + stock options The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options. 🎁 Benefits * Generous Holiday and Time off Policy * Health Insurance options including Medical, Dental, Vision * Work From Home Support * Home office setup allowance * Monthly allowance for cell phone and internet * Care benefits * Monthly allowance for wellness * Annual allowance towards Childcare * Lifetime benefit for family planning, such as adoption or fertility expenses * Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally * Monthly allowance to dogfood the app * All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). * Parental Leave * 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. 💛 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce. Compensation Range: $245K - $345K

Job DescriptionResearch Intern (PhD), Machine Learning Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD. * You will contribute to the development of novel machine learning approaches for biological data analysis and interpretation * You will design and implement experiments to evaluate and improve AI models using large-scale biological datasets * You will collaborate with our interdisciplinary team to tackle complex challenges in molecular biology and drug discovery * You will present your research findings and contribute to publications in top-tier conferences and journals * You will have the opportunity to work on projects that directly impact the future of medicine and biotechnology Who We're Looking For * You are currently pursuing a PhD in Machine Learning, Computer Science, Computational Biology, or a related field * You have a strong background in deep learning, with experience in frameworks such as PyTorch or TensorFlow * You have a proven track record of research, demonstrated by publications at conferences such as NeurIPS, ICML, ICLR, or relevant computational biology venues * You are proficient in Python and have experience with large-scale data processing and analysis * You have excellent problem-solving skills and the ability to work independently on complex research problems * You are passionate about applying AI to solve real-world challenges in biology and medicine * You have strong communication skills and can effectively present technical concepts to diverse audiences * You thrive in a fast-paced, startup environment and are excited about making a significant impact in a growing field Bonus Points * Experience with biological data analysis or computational biology projects * Familiarity with generative AI models, such as transformers or diffusion models * Contributions to open-source machine learning or bioinformatics projects Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage

Job DescriptionCompany Description On-Site 1yr contract $10950/month About the Role We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure. You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value. Job Description • Design and develop algorithms for generative models using deep learning techniques, • Design and build LLM-powered applications for internal and/or customer-facing use cases, • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems, • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration, • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate, • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability, • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies, • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices, • Build monitoring, observability, and feedback loops for model and application performance in production, • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems, • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities, • Mentor other engineers and contribute to architecture, technical direction, and engineering best practices Qualifications • Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience, • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production, • Strong programming skills in Python and experience with backend/API development, • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design, • Experience in optimizing RAG pipelines using both structured and unstructured data, • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent, • Experience in generative AI techniques such as GANs, and VAEs, • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search, • Experience with cloud platforms such as AWS, GCP, or Azure, • Experience with Docker, Kubernetes, CI/CD, and production deployment practices, • Strong understanding of software architecture, scalability, reliability, and distributed systems, • Experience building evaluation, testing, and monitoring for AI systems, • Strong communication skills and ability to work closely with technical and non-technical stakeholder Preferred Qualifications • Experience fine-tuning or adapting open-source LLMs, • Advanced knowledge of natural language processing for text generation tasks, • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks, • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar, • Experience building multi-agent systems or advanced orchestration workflows, • Experience with AI safety, guardrails, red-teaming, privacy, and governance, • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems, • Experience in customer-facing or enterprise SaaS products, • Experience in semiconductor/manufacturing, retail and e-commerce sectors Additional Information All your information will be kept confidential according to EEO guidelines.

Job Description Machine Learning Engineer / AI Engineer Newark, NJ Salary: $120,000 – $180,000 Description / Position Overview This role owns the design, deployment, and long-term performance of production machine learning systems that power data-driven products and operational intelligence. The Machine Learning Engineer is responsible for translating business problems into scalable AI solutions. This includes building end-to-end pipelines, deploying models into production environments, and continuously improving model performance. This is an engineering execution role, not a research-only position. Success requires the ability to move models from experimentation to reliable production systems that drive measurable product and operational impact. Requirements • Experience building and deploying machine learning models in real-world production environments, • Strong Python programming capability and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, • Understanding of statistics, probability, and optimization techniques used in machine learning systems, • Experience working with large-scale structured and unstructured datasets, • Experience deploying and operating models on cloud platforms such as AWS, GCP, or Azure, • Ability to build and manage scalable data pipelines supporting ML workflows, • Strong collaboration skills working with product, engineering, and data teams Responsibilities Machine Learning Development • Design, train, and optimize machine learning models for real-world business applications, • Build end-to-end ML pipelines including data ingestion, preprocessing, training, and evaluation, • Select appropriate algorithms and modeling approaches based on problem context, • Continuously improve model performance through experimentation and iteration Production Deployment & Infrastructure • Deploy machine learning models into scalable production environments, • Build APIs and services that operationalize machine learning capabilities inside products and systems, • Manage the full model lifecycle including monitoring, retraining, and drift detection, • Ensure reliability, scalability, and maintainability of ML infrastructure Data & Engineering Execution • Work with structured and unstructured data sources to support model development, • Implement feature engineering strategies that improve model accuracy and reliability, • Collaborate with data engineering teams to maintain clean and scalable data infrastructure, • Optimize model performance and resource efficiency in production systems Cross-Functional Collaboration • Partner with product and engineering teams to translate business needs into machine learning solutions, • Communicate technical insights and model behavior to non-technical stakeholders, • Contribute to AI roadmap planning and prioritization of ML initiatives Must-Haves • Proven experience deploying machine learning models into production environments, • Strong Python and ML framework expertise (TensorFlow, PyTorch, or Scikit-learn), • Experience building scalable ML pipelines and APIs, • Experience working with cloud infrastructure (AWS, GCP, or Azure), • Strong understanding of statistical modeling and machine learning fundamentals Final Invitation to Apply If you are a hands-on machine learning engineer who thrives on building real-world AI systems and taking models from concept to production impact, this is an opportunity to own meaningful technology that drives product innovation and operational performance. Contact Email Resume: Apply Online: Refer a friend, get up to $1000!

Job Description Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales — from molecules to organisms — enabling us to predict, understand, and program living systems in ways never before possible. Output Biosciences is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI and biology, and backed by top VCs including Y Combinator. As a Machine Learning Research Scientist, Interpretability, you'll work alongside our founders and team members to develop AI systems capable of processing and reasoning across multiple biological data modalities simultaneously. * You will develop specialized methods for understanding our biological reasoning models, reverse-engineering how they represent and process complex biological information. * You will design and conduct experiments to uncover interpretable features across biological scales. * You will address unique challenges in biological model interpretation, such as disentangling the multi-scale, hierarchical representations of biological systems * You will build biology-specific visualization tools that can map model activations to meaningful biological concepts. Who We're Looking For: * You have a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a relevant technical field. * You have a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. * You have a strong publication record in top-tier AI conferences or journals (e.g., NeurIPS, ICML, ICLR). * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX). Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges. * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and taking pride in solving them. * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty. * You have excellent communication skills and can clearly articulate complex technical concepts. * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity. Bonus points: * You have experience applying machine learning to biological or chemical problems. * You have knowledge of physics, molecular biology, chemistry, computational biology, bioinformatics, cheminformatics, or related fields. * You have experience with multi-modal learning. * You have contributed to open-source machine learning projects/ * You have experience in developing efficient code in C/C++. Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $120K - $250K

Job Description Location: New York Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a high-growth AI cybersecurity company backed by top-tier investors and strategic AI leaders. The company is building the security layer for the AI era, protecting enterprises against AI-powered threats such as deepfakes, smishing, and synthetic voice attacks. Following a major Series B funding round led by industry-leading AI and venture partners, the company is entering a critical growth phase. Trusted by major banks, technology companies, and healthcare organizations, they are scaling rapidly to meet enterprise demand in a $200B+ market opportunity. We are looking for a Head of Machine Learning to define and build the companys ML capabilities from the ground up. ML is central to the product vision. This role is not about incremental optimization — it is about owning the strategy, infrastructure, and execution of machine learning across the organization. There is currently no dedicated ML infrastructure or ML team. You will establish the foundations: define where ML drives product value, design production systems end-to-end, and set the technical direction for how ML evolves across the company. This is a high-impact, highly autonomous role suited for someone who has built ML systems in production and is ready to architect an ML function from zero to scale. What Youll Do * Define the companys ML strategy: where ML should be applied across products, what infrastructure is required, and how to approach build vs. buy decisions. * Design and build production ML systems end-to-end — including data pipelines, model training workflows, evaluation frameworks, and inference serving. * Establish rigorous evaluation methodology to measure model quality, detect regressions, and support data-driven iteration. * Own the data strategy: determine what data is needed, how it should be labeled, how feedback loops are structured, and how models continuously improve. * Partner closely with product and backend engineers to integrate ML into customer-facing systems. * Write production-quality code within the existing codebase and contribute to architectural decisions. * Over time, help recruit, mentor, and lead the ML team as the function expands. What Were Looking For * 8+ years of experience building ML systems in production environments. * Experience standing up ML infrastructure at an early-stage startup or serving as the senior/lead ML engineer at a company. * Strong software engineering fundamentals with production experience in languages such as Python, Java, or TypeScript. * Experience with cloud-based ML infrastructure (e.g., SageMaker, Bedrock, Modal, Baseten, or similar platforms). * Hands-on experience with ML and data frameworks such as PyTorch, TensorFlow, Spark, or equivalent tools. * Comfortable working across the stack — infrastructure, backend systems, and data platforms. * Demonstrated ability to mentor engineers and elevate technical standards within a team. * High autonomy and ownership mindset, with the ability to define direction and execute without predefined playbooks. Bonus Points * Experience building ML systems for security, fraud detection, or adversarial environments. * Experience working with LLMs in production (evaluation, fine-tuning, retrieval systems, guardrails). * Background in real-time inference systems or high-throughput distributed systems. * Experience making strategic build vs. buy infrastructure decisions. * Previous startup experience in high-growth environments. Why This Role Will Pivot Your Career * Strategic AI backing: Supported by leading AI and venture investors shaping the future of AI infrastructure and cybersecurity. * Founding-level impact: Build and define the ML function from zero in a company where ML is core to product value. * Enterprise traction: Products already trusted by major banks, tech firms, and healthcare organizations. * Massive market opportunity: Positioned in a rapidly expanding AI cybersecurity space. * Leadership path: Opportunity to evolve into Head of ML as the organization scales. * Ownership & autonomy: Direct influence over architecture, infrastructure, and long-term technical direction. Benefits * Competitive salary & equity options * Health, Dental, and Vision * 401k * Hybrid flexibility Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Job Description Location: New York Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a high-growth AI cybersecurity company backed by top-tier investors and strategic AI leaders. The company is building the security layer for the AI era, protecting enterprises against AI-powered threats such as deepfakes, smishing, and synthetic voice attacks. Following a major Series B funding round led by industry-leading AI and venture partners, the company is entering a critical growth phase. Trusted by major banks, technology companies, and healthcare organizations, they are scaling rapidly to meet enterprise demand in a $200B+ market opportunity. We are looking for a Director of Machine Learning to define and build the companys ML capabilities from the ground up. ML is central to the product vision. This role is not about incremental optimization — it is about owning the strategy, infrastructure, and execution of machine learning across the organization. There is currently no dedicated ML infrastructure or ML team. You will establish the foundations: define where ML drives product value, design production systems end-to-end, and set the technical direction for how ML evolves across the company. This is a high-impact, highly autonomous role suited for someone who has built ML systems in production and is ready to architect an ML function from zero to scale. What Youll Do * Define the companys ML strategy: where ML should be applied across products, what infrastructure is required, and how to approach build vs. buy decisions. * Design and build production ML systems end-to-end — including data pipelines, model training workflows, evaluation frameworks, and inference serving. * Establish rigorous evaluation methodology to measure model quality, detect regressions, and support data-driven iteration. * Own the data strategy: determine what data is needed, how it should be labeled, how feedback loops are structured, and how models continuously improve. * Partner closely with product and backend engineers to integrate ML into customer-facing systems. * Write production-quality code within the existing codebase and contribute to architectural decisions. * Over time, help recruit, mentor, and lead the ML team as the function expands. What Were Looking For * 8+ years of experience building ML systems in production environments. * Experience standing up ML infrastructure at an early-stage startup or serving as the senior/lead ML engineer at a company. * Strong software engineering fundamentals with production experience in languages such as Python, Java, or TypeScript. * Experience with cloud-based ML infrastructure (e.g., SageMaker, Bedrock, Modal, Baseten, or similar platforms). * Hands-on experience with ML and data frameworks such as PyTorch, TensorFlow, Spark, or equivalent tools. * Comfortable working across the stack — infrastructure, backend systems, and data platforms. * Demonstrated ability to mentor engineers and elevate technical standards within a team. * High autonomy and ownership mindset, with the ability to define direction and execute without predefined playbooks. Bonus Points * Experience building ML systems for security, fraud detection, or adversarial environments. * Experience working with LLMs in production (evaluation, fine-tuning, retrieval systems, guardrails). * Background in real-time inference systems or high-throughput distributed systems. * Experience making strategic build vs. buy infrastructure decisions. * Previous startup experience in high-growth environments. Why This Role Will Pivot Your Career * Strategic AI backing: Supported by leading AI and venture investors shaping the future of AI infrastructure and cybersecurity. * Founding-level impact: Build and define the ML function from zero in a company where ML is core to product value. * Enterprise traction: Products already trusted by major banks, tech firms, and healthcare organizations. * Massive market opportunity: Positioned in a rapidly expanding AI cybersecurity space. * Leadership path: Opportunity to evolve into Head of ML as the organization scales. * Ownership & autonomy: Direct influence over architecture, infrastructure, and long-term technical direction. Benefits * Competitive salary & equity options * Health, Dental, and Vision * 401k * Hybrid flexibility Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Job DescriptionRadical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability. The opportunityThe vision for this opportunity is to create an intelligent system that operates in an experimental material science setting. Your core responsibility will be to lead the development of an agentic system for materials development, enhancing reasoning and planning throughout the development process, encompassing data acquisition, model evaluation, pre- and post-training, supervised fine-tuning, reward modeling, and reinforcement learning to drive overall performance of the system. Your expertise will contribute to the broader research community through publications in top-tier AI/ML venues like NeurIPS, ICML, and ICLR, alongside active participation in conferences and workshops. This role offers the unique opportunity to mentor and guide junior members of our technical team and research interns, fostering a culture of growth and innovation. Positions are available at various levels of seniority: Senior, Staff, and Principal.Mission • Drive the development of a system that can pursue complex, multi-objective goals in materials design with limited direct supervision, leveraging agents and multi-agents that can interact with third-party and in-house integrations, including APIs, code interpreters, and hardware components., • Leverage various LLM architectures and models to balance reasoning and continuous adaptation towards intelligent decision-making., • Synthesize large-scale, high-quality (multi-modal) data through methods such as rewriting, augmentation, and generation to improve the abilities of models in various stages., • Work in collaboration with various teams, in particular the experimental materials science team., • Develop and apply reliable evaluation methods to analyze model performance at different stages, uncover the mechanisms and origins of their capabilities, and leverage these insights to enhance model development., • Contribute to the AI and materials science research community through publications and active engagement in top-tier AI/ML venues like NeurIPS, ICML, ICLR, and our company blog, alongside active participation in conferences and workshops., • The ability to tackle challenging problems with new and different ideas, creativity and contrarian thinking., • Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.About you, • Ph.D., M.S., or B.S. in Computer Science, AI, Machine Learning, Applied Maths, or a closely related field, with a strong focus on LLMs., • At least 3 years of research experience in AI, with a proven track record of designing agentic systems., • Familiarity with large-scale model training., • Proficiency in Python and relevant ML libraries (e.g., PyTorch)., • Strong publication record in top-tier AI/ML conferences or journals., • Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.Pluses, • Passionate about leveraging ML for science related problems and a commitment to doing world-class research., • Domain knowledge of materials and/or molecules., • Familiarity with large-scale model training., • Experience with LLM engineering., • Active involvement in the AI research community, with contributions beyond publications, such as organizing workshops or giving talks at conferences.What we offer, • A competitive compensation package also includes the best in benefits:, • Medical, dental, and vision insurance for you and your family, • Mental health and wellness support, • Unlimited PTO and 14+ company holidays per year, • 401K, • Work closely with a team on the cutting edge of AI research. Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.

Job Description Basic Qualifications: • Knowledge of different compilation steps (and ability to fix) in languages such as Go, C, C++, or Java., • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Ability to lead projects with several cross-org dependencies and design complexities, • Large-scale training using data structures and algorithms, • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning) Preferred Qualifications • PhD or equivalent in Computer Science, Engineering, Mathematics or related field, • 8+ years of experience in professional software development experience, developing and deploying systems in production environments, • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib, • Excellent communication skills and the ability to collaborate effectively with cross-functional teams, • Ability to mentor and grow a group of other Software Engineers, • Anomaly Detection Techniques, • Deep Learning, • Scalable ML architecture, • Feature management, • Causal ML, • Reinforcement learning Anticipated base 250-280k + bonus + equity and comprehensive benefits

Job Description Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone. We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. More about us Product (Captions by Mirage) Research (Seeing Voices, technical-white-paper) Updates (Mirage on X / twitter) TechCrunch, Forbes AI 50, Fast Company (press) Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role Mirage is seeking a Research Engineer to build and scale the systems powering our video generation models. You’ll work closely with researchers to optimize performance, improve efficiency, and bring cutting-edge models into production. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. Responsibilities * Train and optimize large-scale video and multimodal models * Improve efficiency across training and inference (memory, latency, cost) * Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation * Build and maintain distributed training systems * Optimize GPU utilization, parallelism, and throughput * Develop tooling for experimentation, evaluation, and debugging * Translate research models into robust, production-ready systems * Monitor and improve model performance in real-world usage What makes you a great fit * 2+ years of professional industry experience * Strong experience in deep learning systems and infrastructure * Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.) * Experience scaling and optimizing large models under low-latency inference constraints * Strong debugging and performance profiling skills * Ability to move quickly from prototype to production * Strong software engineering fundamentals Benefits: * Comprehensive medical, dental, and vision plans * 401K with employer match * Commuter Benefits * Catered lunch multiple days per week * Dinner stipend every night if you're working late and want a bite! * Grubhub subscription * Health & Wellness Perks * Multiple team offsites per year with team events every month * Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $175K - $275K

Job DescriptionAbout Fusemachines Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government. Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI. About the Role A Lead Data Scientist is responsible for designing and implementing data-driven solutions to complex business problems. The role requires extensive experience in data analysis, agentic AI, statistical modeling, machine learning, and data visualization, as well as the ability to lead a team of data scientists and collaborate with cross-functional teams. Responsibilities • Team Leadership: Lead a team of data scientists to develop innovative solutions to complex business problems. Mentor and develop the skills of junior data scientists and provide feedback and guidance to help them improve their work., • Collaboration: Collaborate with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers to develop and implement data-driven solutions., • Strategic Assessment: Assess the business needs of clients and identify areas where AI can be used to improve processes, reduce costs, or increase revenue., • Solution Design: Design and implement statistical models, machine learning algorithms, predictive analytics models, and agentic systems to solve business problems., • Communication: Communicate technical insights and recommendations to non-technical stakeholders in a clear and concise manner., • Continuous Learning: Stay up-to-date with the latest developments in data science, machine learning, and artificial intelligence, and apply new technologies and techniques to solve business problems., • Pipeline Management: Responsible for developing, implementing, and managing end-to-end machine learning pipelines. This will involve building, deploying, and maintaining machine learning models, as well as ensuring data quality and system stability. Requirements for the Role, • Education: Bachelor's, Master's, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field., • Experience: 6+ years of total experience in Data Science, Machine Learning & Generative AI., • Cloud Computing: 4+ years of hands-on experience with AWS, including deep expertise in deploying models and managing compute environments., • IBM WatsonX: 2+ years of hands-on experience with IBM WatsonX, • Agentic AI Tools: Experience with LangGraph, Google ADK or similar., • Agentic Architectures : Experience with advanced RAG & multi-agent systems., • Programming: Strong programming skills in languages such as Python, R, C++, and SQL., • Frameworks: Hands-on experience with ML frameworks, such as PyTorch or TensorFlow. XDOyWllq0r

Job DescriptionTagup is a defense technology company founded at MIT that is redefining logistics superiority with next-generation AI. We’re growing rapidly and are looking for change-makers passionate about delivering innovative technologies to solve the most challenging problems in the world’s highest stakes environments. This is an exciting opportunity to engage in meaningful work that strengthens national security and contributes to the success of U.S. and allied forces. Join us in shaping the future of defense logistics for a safer tomorrow. We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems. In this role, you’ll go beyond building models — you’ll design, deploy, and scale AI solutions that directly support mission-critical operations. This is not a typical ML position. You’ll work at the intersection of cutting-edge research and real-world application, creating models and infrastructure that deliver measurable improvements in reliability, efficiency, and performance. If you’re motivated by solving complex technical challenges and want your work to make a tangible impact on national security and aviation safety, we want to hear from you.What You’ll Do • Develop, train, and optimize ML models for large-scale applications., • Build pipelines for data ingestion and model deployment., • Work with engineers and subject-matter experts to refine solutions., • Conduct testing and validation to ensure reliability., • Co-author technical reports on data analysis and model performance., • Continuously improve ML infrastructure and workflows., • Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.What We’re Looking For, • 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow., • Proven ability to deploy ML models into production and work with large, complex datasets., • Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines., • Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible.

Job DescriptionWe deliver technology to some of the best startups and companies in the world through diverse empowered teams of technologists that want to create change in the digital world.We are an organization that was created to be a safe place for all people from all areas of life. A place where teams are gender-balanced and compensated equally. And a place where careers are unrestrained regardless of cultural, educational, or geographical background. We value people with strong technical skills that are collaborative, curious, results-driven, and take ownership. We embrace people that want to be themselves, have daily flexibility, grow, learn, and make a difference wherever the opportunity presents itself. So we hope this sounds like you. Because we are always looking for exceptional Senior Applied Scientist Engineers to work in immersive client projects that will challenge your abilities. This position requires: Role Summary We are seeking a Senior Applied Scientist to design and deploy AI systems and agentic workflows that safely automate document understanding and decision-making across FOIA, Privacy Act, eDiscovery, and Data Breach workflows. This role focuses on applied AI for high-risk, regulated documents, where systems must make or assist decisions related to review, classification, entity extraction, redaction, and disclosure, while remaining explainable, policy-aware, auditable, and defensible. You will work above core OCR and ingestion pipelines, transforming document content, metadata, layout, policy rules, and reviewer behavior into bounded automation that can be trusted in production. You will help define what decisions can be automated, under what conditions, and with what safeguards. What You’ll Own Automation of Document Decisions Design AI systems that safely automate or assist decisions related to: • Document review, including:, • Responsiveness and relevance, • Privilege and confidentiality, • Sensitivity and disclosure risk, • Entity and data extraction, including:, • Identifying, normalizing, and consolidating people, organizations, locations, and attributes, • Resolving entities across documents and datasets, • Redaction decisions, including:, • What information requires protection, • Where and how it should be applied, • Under which legal or policy authority Define automation boundaries and confidence thresholds, including: • Auto-apply vs. recommend vs. require human review, • Document-, page-, and entity-level decision logic Applied GenAI, Agentic Workflows & Document Intelligence • Build LLM-powered workflows for:, • Document and case summarization with citations and traceability, • Review assistance for responsiveness, privilege, and confidentiality, • Redaction and extraction rationale generation (the “why” behind decisions), • Implement guardrails and grounding to ensure GenAI outputs remain accurate, explainable, and policy-aligned Policy-Aware AI Systems • Translate legal and regulatory requirements into clear, testable AI behavior, • Align systems with:, • Data breach impact assessment and notification workflows, • Partner with legal, privacy, and compliance stakeholders to validate and refine decision logic Quality Assurance, Trust & Defensibility • Monitor model performance, drift, and automation outcomes in production, • Ensure all decisions are traceable, explainable, and defensible for audits, litigation, and public scrutiny Cross-Functional Leadership • Collaborate with Product, Engineering, Legal, Privacy, and Operations teams, • Influence product direction across Legal, Breach, and Government markets, • Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field, • 5+ years of experience building and deploying applied ML / NLP systems in production, particularly for document understanding, classification, or extraction, • 2+ years of hands-on experience with large language models or modern GenAI techniques, including prompt design, RAG pipelines, or LLM-assisted workflows, • Experience building explainable, auditable AI systems, • Experience designing human-in-the-loop automation, • Comfortable working in ambiguous, high-risk environments, • Experience with FOIA, Privacy Act, HIPAA, GDPR, or breach response workflows, • Background in eDiscovery, legal tech, or regulated government systems, • Prior technical leadership or mentoring experience, • Experience scaling AI systems to millions of documents or pages A happy team makes a huge difference, that's why we provide: * Payment in USD or in your local currency * A truly flexible work schedule * Holiday and performance bonuses * An excellent paid time off policy * 4 free Udemy courses a year * Home exercise & wellness membership * An opportunity for you to help create change in the industry * And more! ATHENAWORKS is an inclusive safe organization that only considers your technical ability, work experience, ability to collaborate, your capacity to grow to the next level of your career, and ability to deliver great work. This means that we also embrace/welcome self-taught people as well! We will NEVER consider any other personal or professional aspects of your life. We hope that you choose to have a conversation with us today and find out what makes us different from any company that you have experienced.

Job Description Location: US Remote Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a high-growth AI cybersecurity company backed by top-tier investors and strategic AI leaders. The company is building the security layer for the AI era, protecting enterprises against AI-powered threats such as deepfakes, smishing, and synthetic voice attacks. Following a major Series B funding round led by industry-leading AI and venture partners, the company is entering a critical growth phase. Trusted by major banks, technology companies, and healthcare organizations, they are scaling rapidly to meet enterprise demand in a $200B+ market opportunity. We are looking for a Staff Machine Learning Engineer to define and build the companys ML capabilities from the ground up. ML is central to the product vision. This role is not about incremental optimization — it is about owning the strategy, infrastructure, and execution of machine learning across the organization. There is currently no dedicated ML infrastructure or ML team. You will establish the foundations: define where ML drives product value, design production systems end-to-end, and set the technical direction for how ML evolves across the company. This is a high-impact, highly autonomous role suited for someone who has built ML systems in production and is ready to architect an ML function from zero to scale. What Youll Do * Define the companys ML strategy: where ML should be applied across products, what infrastructure is required, and how to approach build vs. buy decisions. * Design and build production ML systems end-to-end — including data pipelines, model training workflows, evaluation frameworks, and inference serving. * Establish rigorous evaluation methodology to measure model quality, detect regressions, and support data-driven iteration. * Own the data strategy: determine what data is needed, how it should be labeled, how feedback loops are structured, and how models continuously improve. * Partner closely with product and backend engineers to integrate ML into customer-facing systems. * Write production-quality code within the existing codebase and contribute to architectural decisions. * Over time, help recruit, mentor, and lead the ML team as the function expands. What Were Looking For * 8+ years of experience building ML systems in production environments. * Experience standing up ML infrastructure at an early-stage startup or serving as the senior/lead ML engineer at a company. * Strong software engineering fundamentals with production experience in languages such as Python, Java, or TypeScript. * Experience with cloud-based ML infrastructure (e.g., SageMaker, Bedrock, Modal, Baseten, or similar platforms). * Hands-on experience with ML and data frameworks such as PyTorch, TensorFlow, Spark, or equivalent tools. * Comfortable working across the stack — infrastructure, backend systems, and data platforms. * Demonstrated ability to mentor engineers and elevate technical standards within a team. * High autonomy and ownership mindset, with the ability to define direction and execute without predefined playbooks. Bonus Points * Experience building ML systems for security, fraud detection, or adversarial environments. * Experience working with LLMs in production (evaluation, fine-tuning, retrieval systems, guardrails). * Background in real-time inference systems or high-throughput distributed systems. * Experience making strategic build vs. buy infrastructure decisions. * Previous startup experience in high-growth environments. Why This Role Will Pivot Your Career * Strategic AI backing: Supported by leading AI and venture investors shaping the future of AI infrastructure and cybersecurity. * Founding-level impact: Build and define the ML function from zero in a company where ML is core to product value. * Enterprise traction: Products already trusted by major banks, tech firms, and healthcare organizations. * Massive market opportunity: Positioned in a rapidly expanding AI cybersecurity space. * Leadership path: Opportunity to evolve into Head of ML as the organization scales. * Ownership & autonomy: Direct influence over architecture, infrastructure, and long-term technical direction. Benefits * Competitive salary & equity options * Health, Dental, and Vision * 401k * Hybrid flexibility Pragmatike is an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

Job DescriptionHinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all. About the Role: The Dating Outcomes group is responsible for ensuring that people see their most compatible matches, helping them present themselves more effectively, and start meaningful conversations when they match. In short, we help people go on great dates! We are hiring Senior Machine Learning Engineers to help us build the foundations of an AI first dating experience using the latest advancements in the field, leveraging Hinge’s years of preference data. You can expect to build recommendation systems end to end, experiment with using LLMs, photo and mixed input embedding models, as well as build and deploy real-time predictive models that directly impact the experience of millions of users. This is a fast-growing team, and you will have the opportunity to own and define the strategy, vision, and plan for accelerating machine learning at Hinge.Responsibilities • Own and contribute to foundational models that power our recommendations ecosystem., • Contribute to the research and development of models powering Hinge and experiment with the latest innovations in the field of Machine Learning (e.g., LLM agents, MMoE models, VAEs, etc.), • Design, advocate for, and implement solutions that ensure availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters., • Collaborate closely with other Machine Learning engineers, Product Managers, Data Engineers, and Scientists to understand our users' needs and identify opportunities to make their experience better through machine learning., • Mentor and educate Machine Learning Engineers on current and SOA research, technologies, and best practices of practicing machine learning at scale.What We're Looking For, • Strong programming skills: Proficiency in languages like Python, Java, or C++, • System design & architecture: Proven track record of training and deploying large scale ML models, especially DNNs. Good understanding of distributed computing for learning, data processing, and inference., • Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, Databricks, KubeFlow, or W&B is a plus., • ML knowledge: Deep understanding of DNN architectures, track record of building, debugging, and fine-tuning models. Familiarity with PyTorch, TF, knowledge distillation, and recommender systems is a plus., • DevOps skills: The ability to establish, manage, and use data and compute infrastructure such as Kubernetes and Terraform., • Data engineering knowledge: Skills in handling and managing large datasets, including data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow., • Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds., • Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation, • Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes., • 4+ years of experience, depending on education, as a Machine Learning Engineer., • 2+ years of experience working in a cloud environment, such as GCP, AWS, or Azure, and with DevOps tooling, including Kubernetes., • 2+ years of experience designing and developing online and production grade machine learning systems., • 1+ year of experience leading projects with at least 1 other team member through completion. #Hinge

Job Description Location: Cambridge, MA (Eastern Time / UTC -4) Relocation package available Start date: ASAP Languages: English (required) About the Role Pragmatike is hiring on behalf of a fast-growing AI startup recognized as a Top 10 GenAI company by GTM Capital, founded by MIT CSAIL researchers. We are seeking a Staff / Principal ML Ops Engineer to lead the design, implementation, and scaling of the companys ML infrastructure and production AI systems. This is a high-impact, architecture-defining role where youll work across the entire model lifecycletraining, evaluation, deployment, observability, and continuous optimization. You will partner closely with AI researchers, GPU systems engineers, backend teams, and product stakeholders to ensure the companys large-scale AI systems are robust, efficient, automated, and production-grade. This role is ideal for someone who has already built and owned ML platforms at scale and can drive strategy as well as hands-on execution. What Youll Do • Architect, build, and scale the end-to-end ML Ops pipeline, including training, fine-tuning, evaluation, rollout, and monitoring., • Design reliable infrastructure for model deployment, versioning, reproducibility, and orchestration across cloud and on-prem GPU clusters., • Optimize compute usage across distributed systems (Kubernetes, autoscaling, caching, GPU allocation, checkpointing workflows)., • Lead the implementation of observability for ML systems (monitor drift, performance, throughput, reliability, cost)., • Build automated workflows for dataset curation, labeling, feature pipelines, evaluation, and CI/CD for ML models., • Collaborate with researchers to productionize models and accelerate training/inference pipelines., • Establish ML Ops best practices, internal standards, and cross-team tooling., • Deep hands-on experience designing and operating production ML systems at scale (Staff/Principal-level expected)., • Strong background in ML Ops, distributed systems, and cloud infrastructure (AWS, GCP, or Azure)., • Proficiency with Python and familiarity with TypeScript or Go for platform integration., • Expertise in ML frameworks: PyTorch, Transformers, vLLM, Llama-factory, Megatron-LM, CUDA / GPU acceleration (practical understanding), • Strong experience with containerization and orchestration (Docker, Kubernetes, Helm, autoscaling)., • Deep understanding of ML lifecycle workflows: training, fine-tuning, evaluation, inference, model registries., • Experience deploying and operating LLMs and generative models in production at enterprise scale., • Familiarity with DevOps, CI/CD, automated deployment pipelines, and infrastructure-as-code., • Experience optimizing GPU clusters, scheduling, and distributed training frameworks., • Prior startup experience or comfort operating with ambiguity and high ownership., • Research pedigree: MIT CSAIL founders recognized for breakthrough AI and systems contributions., • Customer impact: Deploy AI solutions powering Fortune 500 clients., • Industry momentum: Lab alumni have led high-value acquisitions (MosaicML Databricks, Run:AI Nvidia, W&B CoreWeave)., • Funding & growth: Oversubscribed seed round, next funding in 2026., • Career growth & influence: Lead AI initiatives, optimize pipelines, and directly impact production AI systems at scale., • Culture & autonomy: Own critical systems while collaborating with world-class engineers., • Competitive salary & equity options, • Sign-on bonus, • Health, Dental, and Vision

Job DescriptionQuantitative Software Engineer | Intelligent Systems & Architecture Location: New York Metropolitan Area (Stealth) Total Compensation: $400,000 – $850,000+ (Aggressive performance-based upside) The Firm We are a premier, research-driven investment firm operating at the intersection of extreme-scale computing and mathematical finance. We do not follow the market; we model its underlying reality. We are seeking a Quantitative Software Engineer to architect the next generation of our autonomous intelligence platform. The Mandate In this role, you aren't just writing code; you are building the firm's primary engine for alpha generation. You will sit at the nexus of high-performance systems and advanced machine learning, responsible for the end-to-end delivery of mission-critical trading infrastructure. • Architect & Scale: Design high-throughput, low-latency distributed systems capable of training and deploying complex models on petabytes of real-time data., • Engineer Intelligence: Bridge the gap between theoretical research and production-grade execution by optimizing neural architectures for high-stakes financial environments., • Academic Excellence: A Bachelor's or Master's in Computer Science from a global Top-Tier institution (the 0.1% of your graduating class)., • Elite Technical Experience: A background at a Tier-1 technology firm leading high-impact initiatives in AI, Large Language Models (LLMs), or large-scale distributed systems., • Founder Mindset: Preference for those who have founded a technology startup or held a leadership role in an early-stage, high-growth venture. We value the "full-stack" ownership and the ability to solve ambiguous problems without a playbook., • Systemic Mastery: Expertise in high-performance languages (C++, Java) and modern AI frameworks (Python, PyTorch). You have a visceral understanding of how to optimize code for both speed and scale., • Fintech Intuition: A background in high-growth fintech or systematic trading is an advantage, but we value raw intellectual horsepower and engineering elegance above all else.Why This is the Apex Opportunity, • Direct P&L Impact: Unlike Big Tech, where your impact is diluted across millions of users, your work here directly dictates the firm's success. Your compensation is mathematically tied to the value you create., • Radical Autonomy: We operate in small, highly autonomous "cells." You will have the budget, the compute power, and the freedom to disrupt any part of our stack.

Job Description We are seeking a talented and analytical Data Scientist with 3–5 years of experience to join our team. The ideal candidate will have hands-on experience working with data, building models, and generating insights to support business decision-making across domains such as Retail, Banking, Financial Services, Healthcare, or Insurance. Key Responsibilities: • Analyze large datasets to identify trends, patterns, and actionable insights, • Build and deploy machine learning models for prediction and classification tasks, • Work with structured and unstructured data from multiple sources, • Perform data cleaning, preprocessing, and feature engineering, • Collaborate with business stakeholders to understand requirements and translate them into data solutions, • Develop dashboards and reports to communicate insights, • Validate and monitor model performance and improve accuracy over time, • Work closely with engineering teams to deploy models into production Required Qualifications: • 3–5 years of experience as a Data Scientist or Data Analyst, • Strong programming skills in Python or R, • Experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch), • Strong knowledge of statistics, probability, and data modeling, • Experience with SQL and working with large datasets, • Familiarity with data visualization tools (Tableau, Power BI, or similar) Preferred Skills: • Experience in one of the following domains:, • Retail (customer analytics, recommendation systems), • Banking / Finance (fraud detection, risk modeling), • Healthcare (patient data, predictive analytics), • Insurance (claims analytics, underwriting models), • Experience with big data tools (Spark, Hadoop), • Knowledge of cloud platforms (AWS, Azure, or GCP), • Experience deploying models using APIs or cloud services What We’re Looking For: • Strong analytical and problem-solving skills, • Ability to communicate complex findings in a simple way, • Attention to detail and data accuracy, • Ability to work in a collaborative, fast-paced environment Employment Type: Full-time / Contract (based on project requirements) Company DescriptionWe are a growing staffing and consulting firm specializing in placing skilled professionals across industries such as Banking, Financial Services, Retail, Healthcare, and Insurance. Our focus is on connecting high-quality talent with the right opportunities through a structured and results-driven approach. We work closely with both clients and candidates to ensure strong alignment, offering support throughout the hiring process—from profile optimization and interview preparation to successful onboarding. Our goal is to build long-term partnerships and deliver consistent value through quality placements and reliable execution.We are a growing staffing and consulting firm specializing in placing skilled professionals across industries such as Banking, Financial Services, Retail, Healthcare, and Insurance. Our focus is on connecting high-quality talent with the right opportunities through a structured and results-driven approach.\r\n\r\nWe work closely with both clients and candidates to ensure strong alignment, offering support throughout the hiring process—from profile optimization and interview preparation to successful onboarding. Our goal is to build long-term partnerships and deliver consistent value through quality placements and reliable execution.

Job Description Job Description: Palantir Data Engineer We are seeking a seasoned Data Engineer with 3-7 years of experience in data engineering, cloud platforms and distributed systems, along with 2+ years of hands-on experience with Palantir Foundry/ AIP. The ideal candidate will work on designing scalable data solutions, building robust data pipelines, modelling enterprise datasets and enabling analytics and AI/ML use cases on Palantir Foundry. Experience in the insurance domain is a plus. Location – Jersey City, NJ Key Requirements • 3-7 years of overall experience in data engineering, building and maintaining large-scale data pipelines and platforms., • 2+ years of hands-on experience with Palantir Foundry, including data ingestion, pipeline builder, transformations and working with Foundry datasets and applications., • Experience building interactive applications using Foundry Workshop, Slate and custom frontends using TypeScript., • Proficiency in programming languages such as Python, PySpark, and TypeScript/JavaScript., • Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift)., • Deep understanding of microservices architecture and distributed systems., • Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines., • Experience with big data technologies like Snowflake., • Strong problem-solving and performance optimization skills., • Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes., • Experience working in agile environments delivering complex data engineering solutions., • Palantir Foundry certification or demonstrated project experience is highly preferred., • 3+ years of work experience with Data Engineering, • 2+ years of work experience with Palantir, • 3+ years of work experience with Python (Programming Language)

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. About the Role We're hiring for an experienced ML-focused Data Scientist to own growth-oriented modeling across the customer lifecycle - acquisition, activation, retention, resurrection and monetization. You'll work alongside other data scientist to design, validate, and productionize statistical and ML systems (pLTV, churn/survival, uplift/incrementality, lookalikes, clustering/embeddings, NBA/ranking) that directly drive growth. This is a hands-on role for someone with strong mathematical/statistical foundations, broad modeling experience, and pragmatic MLOps chops who can lead experiments and partner closely with Marketing, Engineering, CRM, and Product. What you'll do… • Lifecycle modeling: Build and maintain predictive LTV, churn (including survival/time-to-event), order-rate, and resurrection models that feed acquisition, CRM, and retention strategies., • Acquisition & lookalikes: Create lookalike / propensity models for paid channels and audience construction; optimize CAC vs LTV tradeoffs., • Next-Best-Action & personalization: Develop NBA/ranking models, small-scale recommenders and embedding-based similarity systems to increase activation and orders., • Unsupervised & representation learning: Lead segmentation, clustering, embeddings and representation work that create actionable cohorts and features., • Production & MLOps: Own the full model lifecycle - training pipelines, CI/CD, model registries, containerized deployment, monitoring, retraining and drift detection; partner with engineers to operationalize models into CRM, marketplace and paid channels., • Model governance & reproducibility: Ensure models are well-tested, explainable, calibrated, and auditable; document assumptions, limitations and business mappings., • Cross-functional influence: Translate technical work into product recommendations, dashboards and clear narratives for Growth, Marketing and Engineering. Mentor peers and raise modeling and MLOps standards.Required qualifications, • 5-8+ years in data science, applied ML or statistics, with a track record of shipping production models., • Strong math & statistics: probability, inference, regression, survival analysis/time-to-event, causal reasoning, and familiarity with statistical modeling tradeoffs., • End-to-end ML experience: experience building, validating and deploying classification/regression/ensemble/deep models; comfort with embeddings and representation learning., • MLOps & production skills: pragmatic experience with model CI/CD, model registries (MLFlow or similar), containerization (Docker), orchestration (Airflow), and runtime infra (K8s / ECS)., • Software engineering & tooling: Python (pandas, scikit-learn, XGBoost/LightGBM, PyTorch/TensorFlow optional), strong code hygiene, testing and reproducibility., • Product & stakeholder collaboration: excellent communication, ability to embed with Growth/CRM/Marketing and translate models into product decisions., • Education: BS in a quantitative field required; MS/PhD in statistics, math, CS, economics or similar preferred.Nice-to-haves, • Experience in subscription marketplaces, food-tech, or consumer marketplaces., • Familiarity with feature stores, Snowflake/BigQuery, and production monitoring tools., • Experience with causal libraries (EconML), uplift frameworks, or survival modeling packages., • Prior work on small-scale recommender systems, embeddings, or NLP personalization. Learn More About CookUnity We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale. We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to a nutritional coach and fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🌟 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$160,000—$185,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description We are a cutting-edge technology company at the forefront of the Artificial Intelligence (AI) revolution. Our mission is to create intelligent solutions that transform industries and drive innovation. We are seeking a talented and motivated Prompt Engineer to join our dynamic team and play a pivotal role in shaping the future of AI. Role Overview: As a Prompt Engineer, you will be a key member of our AI development team, responsible for designing and developing high-quality prompts that drive our AI models and algorithms. Your expertise in crafting effective and engaging prompts will be essential in enhancing the performance and capabilities of our AI systems. Responsibilities: • Collaborate with AI researchers and developers to understand project requirements and objectives., • Design and create a diverse range of prompts tailored to specific AI tasks and applications., • Develop creative and innovative ways to generate effective prompts that improve model performance., • Conduct extensive research to identify and curate relevant data sources for prompt development., • Ensure the prompts are designed to elicit desired responses and achieve the desired outcomes., • Optimize and fine-tune prompts based on continuous testing and feedback from AI models., • Analyze AI model outputs and make data-driven adjustments to improve prompt efficacy., • Stay up-to-date with the latest advancements in natural language processing and AI technologies., • Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred., • Proven experience in working with natural language processing and AI technologies., • Strong understanding of AI models, algorithms, and neural networks., • Experience in prompt engineering, creative writing, or content creation is a plus., • Proficiency in programming languages such as Python or JavaScript., • Solid knowledge of data collection, preprocessing, and annotation for prompt development., • Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging Face., • Strong analytical and problem-solving skills with a keen eye for detail., • Excellent communication and collaboration skills to work effectively in a team environment.

Job Description StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we're here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. The Data Science team, a part of the broader StubHub Data organization, is looking for an experienced, senior-level Data Science Manager to lead a growing team (currently 6, ranging from entry level DS to Staff+) that covers a wide range of data science disciplines. StubHub is the largest secondary ticketing marketplace in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. As a Data Science Manager, you will need to work closely with business leaders and convert their long-term strategic goals into tangible machine learning projects executed by your team at a day-to-day level. Understanding when to provide oversight from a technical perspective, while being able to grow individuals, will be paramount in your team's long-term success. You will also be responsible for the technical and personal growth of your team members, developing talent density through focused mentorship, strategic career development, and execution excellence. There will be a need for planning of team structure and growth as we put more investment into ML, especially understanding the best ways of building and applying generative AI solutions within our product. You will be joining at a critical time for the Data Science practice and the company – while the value of this discipline has been established and there's a high performing team in place, we are far from steady state. Key areas of investment from a vision and team planning perspective include establishing new pockets of deep technical expertise (e.g. causal inference, graph ML), advocating for best-in-class ML tooling/platform, and widening the reach of data science company-wide. As a senior leader of this team, you will be in charge of shaping and materializing that vision. Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA What You'll Do • Technical project scoping and planning, • Partner with cross-functional stakeholders across the business, executives, and data team, • Technical review and architecture oversight, • Recruitment and end-to-end talent growth development: Performance reviews, promotion recommendations, 360 feedback, etc, • 8 - 10 years of relevant machine learning/data science in a fast-paced, high growth environment, • 8 - 10 years of experience managing high performant data science team., • Strong programming and analytical ability with expertise in SQL and Python (TensorFlow, scipy, scikit-learn, PyTorch, statsmodels), • Experience with modern workflow orchestration used in machine learning, e.g.,Metaflow, ZenFlow, Airflow, • Nice to Haves, • Worked at a consumer tech company, • Experience with GenAI/LLM/Agentic workflows in a production setting, • Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale., • Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact., • Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed., • Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options. The anticipated gross base pay range is below for this role. Actual compensation will vary depending on factors such as a candidate's qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub's total compensation and competitive benefits package, which includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits. Salary Range$300,000—$400,000 USDAbout UsStubHub is the world's leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the world -- from sports to music, comedy to dance, festivals to theater -- StubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action. For California Residents: California Job Applicant Privacy Notice found hereWe are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.

Job Description The Role Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales. * You will build foundational models for biology capable of reading and writing biology at scale * You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems * You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets * You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization * You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits Who We're Looking For: * You have a Bachelor's in Computer Science, Machine Learning, or a related technical field * You have 3+ years of experience in developing and implementing deep generative learning models * You have experience pre-training models and are proficient in distributed computing environments * You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX) * You have experience with deep learning and generative architectures such as transformers, diffusion models and autoencoders * You are skilled in working with terra-scale datasets and scaling models to billions of parameters * You have a strong understanding of machine learning fundamentals, including various model architectures, optimization techniques, and evaluation metrics * You have experience in designing and implementing efficient data pipelines for processing and managing large datasets * You are experienced in developing robust evaluation frameworks and ensuring data integrity in machine learning projects * You are experienced in code organization, version control, and collaborative software development practices. Who You Are: * You have excellent problem-solving skills and the ability to quickly adapt to new challenges * You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them * You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty * You have excellent communication skills and can clearly articulate complex technical concepts * You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity Bonus points * You have experience applying machine learning to biology or chemistry * You have contributed to open-source machine learning projects or published research papers in the field of AI/ML * You have experience optimizing machine learning models for high-performance computing environments * You are familiar with ML-Ops practices and tools for managing ML experiments and deployments Our Values ❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions. 🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards. 🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community. 📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner. 🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling. What We Offer * We encourage new and different ideas, creativity and contrarian thinking * Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you * You own your day-to-day management. What we care about is that we all hit our milestones * Competitive salary and equity in a growing, well-funded startup * Excellent medical, dental, and vision coverage Compensation Range: $110K - $250K

Job DescriptionCoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at You'll Do: A lab signs with CoreWeave. They have thousands of GPUs waiting. Their first month? Spent on cluster setup instead of research. Building deployment scripts, fighting container images, wiring up job orchestration. They came to train models. Instead, they're doing operations. This is the problem. We're building the Applied Training team to fix it. You'll be an early member of a small team, responsible for our Kubernetes-native research cluster platform, or the sandbox client for agentic training and evaluation, or possibly a new project altogether. The goal is specific: Give every CoreWeave customer the research infrastructure that currently only exists inside frontier labs. About the role: • Contribute to the roadmap for Applied Training. Figure out what actually unlocks new workloads and what's just nice to have. Work directly and closely with customers, and other teams inside of CoreWeave that are building cloud native primitives. Compute, storage, networking, etc., • For the research cluster platform: design and build a complete research cluster experience. CLI, job configuration schema, Kubernetes operators, daemons. Solve the problems researchers actually hit: code distribution, checkpoint-triggered evaluation, cross-cluster scheduling, programmatic job control. Replace the patchwork of scripts customers keep building on their own., • For sandbox infrastructure: own the Python SDK and work in a very tight loop with the backend team. When an RL training run needs to spawn thousands of isolated containers for agent rollouts, that's this system. When someone wants to run agent benchmarks at scale, that's this system. Make it work with our Kubernetes clusters, storage, and auth so researchers don't have to think about infrastructure., • Write the documentation for running popular OSS training frameworks on CoreWeave. The work that can unblock customers and help them succeed., • Work with infrastructure teams and customers directly. The customers are large AI labs running thousands of GPUs. Understand how they structure their internal supercomputing stacks. Bring that knowledge back to what we build.Who You Are:, • 5-8+ years building distributed systems, ML infrastructure, or developer platforms., • Real Kubernetes experience: custom controllers, operators, scheduling, CRDs, workload orchestration at scale. Not just deploying things to Kubernetes or cluster administration., • Excited about rigorous engineering, but enabled by AI based workflows., • You understand what makes researchers productive. Code distribution matters. Fast iteration cycles matter. Workflows that don't require becoming infrastructure experts matter., • Familiarity with training: how distributed jobs get scheduled, how ranks initialize, what breaks at scale., • You've shipped infrastructure that other people rely on daily. Not prototypes. Production systems., • Experience building internal ML platforms or research clusters at a company doing large-scale training., • Familiarity with agentic AI: RL training with rollouts, agent evaluation, sandbox isolation for running untrusted code., • Background with Slurm, Ray, or similar workload orchestration. Opinions on where they fall short., • Experience with container runtimes, isolation (gVisor, Kata), or serverless platforms., • Be Curious at Your Core, • Act Like an Owner, • Empower Employees, • Deliver Best-in-Class Client Experiences The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs, including: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration California Consumer Privacy Act - California applicants only CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job DescriptionAbout Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on . About The Job Mistral AI is seeking an Applied AI Engineer focused on DevOps to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. Applied AI Engineers, ML Infra at Mistral AI work directly with customers to quickly understand their greatest challenges and design and implement AI solutions. In this role, you’ll apply your problem-solving ability, creativity, and technical skills to help organizations use AI to drive real impact in the world. You’ll have the opportunity to gain rare insight into and contribute to some of the most important industries and institutions globally! Applied AI Engineers, ML Infra responsibilities look similar to those of a startup CTO: you’ll work in small teams and own end-to-end execution of high-stakes projects. A day might span discussing architecture with fellow engineers, wrangling massive-scale data, coding a custom web app, speaking with customer executives, or establishing a strategy for the Applied Engineering team. What you will do • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager• Familiarity with AI frameworks such as PyTorch or TensorFlow• Contributions to open-source projects, particularly in the space of DevOps or AI Benefits \uD83D\uDCB0 Competitive salary and bonus structure \uD83D\uDE80 Generous Equity\uD83E\uDDD1️‍⚕️ Health : Competitive Healthcare program \uD83D\uDC74\uD83C\uDFFB Pension : 401K (6% matching)\uD83C\uDFDD️ PTO : 18 days \uD83D\uDE97 Transportation: Reimburse office parking charges, or $120/month for public transport\uD83E\uDD1D Coaching: we offer Betterup coaching on a voluntary basis\uD83C\uDFC0 Sport: $120/month reimbursement for gym membership\uD83E\uDD55 Meal stipend: $400 monthly allowance for meals (solution might evolve as we grow bigger)\uD83C\uDF0E Visa sponsorship

Job DescriptionSchmidt Sciences is a nonprofit organization founded in 2024 by Eric and Wendy Schmidt that works to accelerate scientific knowledge and breakthroughs with the most promising, advanced tools to support a thriving planet. The organization prioritizes research in areas poised for impact including AI and advanced computing, astrophysics, biosciences, climate, and space—as well as supporting researchers in a variety of disciplines through its science systems program. About the AI & Advanced Computing Institute (“AI Institute”) The AI Institute at Schmidt Sciences is a grantmaking and research group that views AI as a transformative force for scientific discovery and societal progress. Over the next decade, we aim to support key researchers who are working to make AI systems competent, trustworthy, reliable, and able to effectively partner with human scientists on the next generation of discovery. We will also make distinctive investments in beneficial AI areas where philanthropy has a unique advantage. By supporting enabling infrastructure, foundational research, and targeted programs in science disciplines, the AI and Advanced Computing Institute will create the conditions for AI-enabled discovery to achieve its promise. The AI Institute currently has three focus areas: AI for Science – using AI to improve how scientists generate hypotheses, conduct experiments, analyze data, and produce new knowledge – and do this in a way that specifically accelerates the discovery process. Exploratory programs include post-transistor hardware for AI and AI for scientific simulation.Science of AI – understanding and controlling AI systems to mitigate and manage potential risks from advanced AI. Improve AI reliability and performance in areas of limited commercial interest. Existing programs include AI2050 and Science of Trustworthy AI. Exploratory programs include AI interpretability and evolution of multi-agent communication.Beneficial AI – providing scientific foundations and datasets for understanding the larger human impacts of AI. This includes selected high-impact grantmaking, such as our programs to use AI to accelerate humanities research (Humanities and AI Virtual Institute), and to quantify the impact of AI on the labor market (AI@Work). Schmidt Sciences has multiple programs related to the AI Institute, such as the Virtual Institute for Scientific Software (VISS), which seeks to accelerate the pace of scientific discovery through the support and development of high-quality, community-oriented scientific software. These philanthropic efforts support experienced engineers who are tasked with building open-source infrastructure and applications for multi-disciplinary, high-performance, at-scale scientific discovery. The Role Reporting to the Compute Program Scientist in the AI Institute, the Software Engineer will provide technical leadership and apply application development expertise across AI Institute and Schmidt Sciences multidisciplinary efforts. The initial set of projects will focus on cutting-edge developments in AI. A successful candidate should have a work portfolio that reflects specific contributions to production-grade software products. Success for this role is defined by the quality of software components produced, and the impact of the programming contributions on the overall success of each project. This role requires up to 30% domestic travel. Example activities for this role:● Implementing recently published algorithms or novel data-processing techniques within an existing application.● Troubleshooting and evaluating complex software packages for numerical accuracy, finding regressions after refactoring, or adopting existing software libraries for new hardware platforms.● Instrumenting research software for performance optimization and analysis, especially for large-scale, distributed workflows.● Using a combination of open source packages and proprietary APIs to construct scalable AI services using hybrid on-prem and cloud-based resources. Key Responsibilities for this role include the following:Primary Technical Development • Select the optimal tools and algorithms to implement solution components that enable new scientific capabilities or mitigate gaps and address test findings., • Own cognizant responsibility for the software architecture of multiple codebases using different programming languages., • Analyze and assess model resource requirements, review operational plans (e.g., virtualization, cloud, etc.), and evaluate other technical opportunities.Additional Schmidt Sciences Support, • Assist existing programs by providing software development expertise and mentorship, while working closely and collaboratively with multiple subject matter expert teams., • Work with other members of the Schmidt Sciences technical team to implement new software features and capabilities in support of diverse research activities., • Maintain awareness and track industry trends for tools and frameworks that address data management, analysis, visualization, monitoring, and security of research applications., • Participate in relevant industry events and forums, representing Schmidt Sciences’ presence on AI and advanced computing issues.Required Knowledge, Skills, and Abilities, • A Bachelor’s degree from an accredited institution, with a focus on Computer Science, Mathematics, or a related field., • 5+ years of professional experience developing high-quality software applications., • Proficiency with software engineering tools and best practices., • Proficiency with modern machine-learning software frameworks, such as JAX, PyTorch, TensorFlow, etc., • Exposure to CPU/GPU/TPU acceleration techniques with popular SDKs (e.g., OpenCL, CUDA, ROCm, Cloud TPU)., • Prior work with containerized Linux workloads, including GPU-accelerated configurations., • Basic knowledge of computer networking and distributed computing., • Ability to design, train, deploy, or maintain state-of-the-art AI models at a production scale., • Experience producing technical writing for expert and general audiences., • Good track record of collaborative impact in high-intensity, team-based environments., • Sense of controlled urgency in driving work to completion., • The highest integrity and ability to maintain confidentiality., • Be able to travel within the U.S. and internationally on a regular basis as needed.Preferred Knowledge, Skills, and Abilities, • Expert-level experience and industry credentials in the software and hardware frameworks that drive modern AI, and competence in at least one, and preferably multiple, fields of science impacted by modern AI., • Exposure to multiple steps in the software design lifecycle, such as evaluating the scalability, data requirements, compute needs, and selecting infrastructure components., • Expertise in relevant technical focus areas, e.g., AI model optimization and hardware accelerated frameworks., • Ability to work with and effectively translate technical concepts across multiple scientific disciplines., • Ability to critically evaluate scientific and technical publications and emerging methods in related disciplines.

Job Description About Cleerly We're Cleerly – a healthcare company that's revolutionizing how heart disease is diagnosed, treated, and tracked. We were founded in 2017 by one of the world's leading cardiologists and are a growing team of world-class engineering, operations, medical affairs, marketing, and sales leaders. We raised $223M in Series C funding in 2022 which has enabled rapid growth and continued support of our mission. In December 2024 we received an additional $106M in a Series C extension funding. Most of our teams work remotely and have access to our offices in Denver, Colorado, New, York, New York, Dallas, Texas, and Lisbon, Portugal with some roles requiring you to be on-site in a location. Cleerly has created a new standard of care for heart disease through value-based, AI-driven precision diagnostic solutions with the goal of helping prevent heart attacks. Our technology goes beyond traditional measures of heart disease by enabling comprehensive quantification and characterization of atherosclerosis, or plaque buildup, in each of the heart arteries. Cleerly's solutions are supported by more than a decade of performing some of the world's largest clinical trials to identify important findings beyond symptoms that increase a person's risk of heart attacks. At Cleerly, we collaborate digitally and use a wide variety of systems. Our people use Google Workspace (GMail, Drive, Docs, Sheets, Slides), Slack, Confluence/Jira, and Zoom Video, prior experience in these areas is a plus. Role or department specific technology needs may vary and will be listed as requirements in the job description. While we are mostly a remote company, travel is required for some team meetings and cross function projects typically once per month or once per quarter, for some roles like sales or external facing roles travel could be up to 90% of the time. About the Opportunity We're seeking a Senior Software Engineer to drive key technical initiatives across our computational imaging pipeline. In this high-impact role, you'll own the complex systems responsible for deploying, scaling, and monitoring our regulated AI algorithms end-to-end. You will influence the architecture of our system, ensuring our solutions meet medical standards for quality and performance, while mentoring other engineers and helping shape our technical culture. About the Team You will join our expert Computational Imaging team, where we develop sophisticated algorithms to enhance and improve medical imaging. We are focused on improving the quality and clinical value of medical images, creating powerful, extra software components that correct artifacts, standardize data, and ensure the utmost precision before the final analysis. Our work is essential for elevating the reliability and accuracy of Cleerly's regulated products. Responsibilities • Design, build, and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms., • Design extensible system architectures and make pragmatic trade-offs that balance performance, security, and maintainability., • Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability., • Ensure high availability and observability of our services; improve alerting, logging, and incident response across the stack., • Set and uphold strong engineering standards via code reviews, technical mentorship, and design documentation., • Lead technical design reviews and system decomposition efforts across teams., • Proactively identify risks and gaps in operational or architectural resilience, and drive durable improvements., • Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation., • Design and implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards, • Contribute to the necessary technical documentation required for regulatory submissions. Requirements • Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent experience)., • 8–12 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar)., • Demonstrable capability in designing, implementing, and securing RESTful web services, • Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes)., • Experience with AWS, GitHub, and continuous integration pipelines, • Proven track record of architecting and delivering scalable systems in production environments., • Experience mentoring engineers and raising the technical bar through reviews and design feedback., • Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability., • Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks)., • Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements., • Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range., • Base Salary: $153,000 - $179,000 Working at Cleerly takes HEART. Discover our Core Values: • H: Humility- be a servant leader, • E: Excellence- deliver world-changing results, • A: Accountability- do what you say; expect the same from others, • R: Remarkable- inspire & innovate with impact OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER. We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation. By submitting your application, you agree to receive SMS messages from Cleerly recruiters throughout the interview process. Message frequency may vary. Message and data rates may apply. You can STOP messaging by sending STOP and get more help by sending HELP. For more information see our Privacy Policy (). All official emails will come from @cleerlyhealth.com email accounts. #Cleerly