Trabajos Engineering en California - Page 14

About the Team OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance human creativity, and solve complex problems. About the Role As a Research Engineer in OpenAI's Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. In this role, you will: * Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. * Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. * Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. * Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. * Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large. You might thrive in this role if you: * Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. * Demonstrated experience in deep learning and transformers models * Proficiency in frameworks like PyTorch or Tensorflow * Strong foundation in data structures, algorithms, and software engineering principles. * Experience with search relevance, ads ranking or LLMs is a plus. * Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization * Excellent problem-solving and analytical skills, with a proactive approach to challenges. * Ability to work collaboratively with cross-functional teams. * Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines * Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this ___. At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. About the team We are the___ team — empowering the people to keep each other better informed, with a___. Community Notes is constantly advancing the state-of-the-art in improving the quality of information on the internet and we employ an experimental, fast-moving, iterative approach to find product solutions that work for people of all different points of view. What You’ll Do: • Design and build improvements to our unique machine learning algorithm that improve Community Notes’ helpfulness, accuracy, scale, speed, and manipulation resistance, • Work in public: contribute to our___, supporting external engineers working with our public data. For (___)., • Build efficient, scalable internal production machine learning systems and infrastructure, • Contribute to the entire product via tight cross-functional collaborations with product/eng/etc Qualifications: • Experience developing and shipping high-impact ML solutions end-to-end: from getting your hands dirty creating training data pipelines, to developing novel model architectures, to deploying to production at scale reliably, • Demonstrated ability to work with real-world data to extract insights, inform product roadmap and develop guiding metrics in situations that lack cut-and-dry evaluation criteria, • Familiarity with one or more deep learning software frameworks, e.g. PyTorch, • Enjoy working in a 0-to-1 space with no known machine learning or product solutions, and trailblazing to build novel solutions that work, • Love doing whatever work is needed to get things done, enabling rapid iteration on the product Annual Salary Range $180,000 - $440,000 USD Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. xAI is an equal opportunity employer.

We are looking for the best At 42dot, our Machine Learning Engineers conduct research and development on machine learning algorithms to ensure safe autonomous driving. We address complex challenges that aren't easily solved through conventional means, aiming to achieve human-level natural autonomous driving. Additionally, we collaborate with various teams across 42dot to leverage machine learning effectively. \n Responsibilities • Dataset and Evaluation: We focus on curating high-quality datasets tailored to autonomous driving scenarios and designing robust evaluation metrics to accurately assess algorithm performance., • Active Learning: Our team explores techniques for efficiently selecting and labeling informative data points, minimizing labeling efforts while enhancing model performance., • Network Architecture Search: We investigate methods for autonomously discovering optimal neural network architectures, specifically tailored for label generation from sensor and video data in autonomous driving contexts., • Transfer/Low-shot/Long-tail Learning: Our efforts include developing strategies to leverage knowledge from related tasks or domains, addressing scenarios with limited labeled data (low-shot learning), and handling class distribution imbalances (long-tail learning) commonly found in autonomous driving datasets., • Efficient Learning and Inference: We optimize learning algorithms and inference processes to ensure resource-efficient utilization, crucial for real-time deployment in autonomous driving systems., • Privacy: Our team prioritizes the development of privacy-preserving techniques, ensuring the handling of sensitive data while maintaining high-performance label generation, in compliance with privacy regulations and safeguarding user information. Qualifications • Minimum of 7 years of relevant experience, • Master's or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field relevant to machine learning, or equivalent experience, • Strong background in Linear Algebra, Probability, Signal Processing, and machine learning concepts, • Proficient programming skills in languages such as C/C++, Python, and others Preferred Qualifications • Experience in development related to autonomous driving and robotics, including Object Detection, Semantic Segmentation, Depth Estimation, and Transformer-based models., • Experience in building and utilizing automated learning pipeline systems., • Track record of publications or contributions in relevant fields, such as CVPR, ICCV, ECCV, NeurIPS, AAAI, etc., • Enjoyment in discovering and solving new problems in the field. \n Please refer to the videos from___ and ___ for insights into 42dot Autonomous Driving, our autonomous driving AI software. Please upload all submission files in PDF format. ※ Please review the following information before applying. ㆍHow to work in 42dot, ___ ㆍHow to work in 42dot, ㆍ42dot's Employee Engagement Program, ___ ㆍ42dot's Employee Engagement Program,

Location: SF or Waterloo, with ability to travel Start Date: Flexible, ideally Q3 2025 ___ is building planetary superintelligence. Backed by top funds, we’ve raised $10M+ and are now heads down building. Join us at the cutting edge, where we’re scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You’ll be at the core of a moonshot journey to define what’s next in agentic AI and frontier model capabilities. We are looking for an experienced Senior Machine Learning Engineer who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands-on experience implementing a wide range of pre-training and post-training models, including large foundation models (beyond just LLM fine-tuning). This role is focused on: * Designing, implementing, and scaling state-of-the-art models * Productionizing research codes, models and technologically complex systems * Shaping benchmark design and model evaluation frameworks * Building agentic AI capabilities and long-term technical bets Hum is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we’re backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations. We’re building multimodal foundation models for the natural world. We believe there’s more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world. The role will involve: * Collaborating with researchers and scientists to implement, evaluate and scale proof-of-concept models. * Owning, implementing and integrating the latest state-of-the-art methods and external open-source codes. * Develop AI systems capable of accurately understanding the universe and generating new knowledge. * Training multi-modal models supporting different sensor and other modalities like text * Bachelor’s degree in computer science, engineering, a related field, or equivalent experience. * 5+ years of relevant work experience. * Prior experience building distributed training pipelines for multi-node systems using PyTorch and Ray. * Experience training large diffusion or transformer models. Preferably on video or time series data. * Proficiency with Python, Ray Trainer, PyTorch, and Anyscale framework. * Familiarity with cloud platforms such as AWS, GCP, or Azure. * Past training of video or time-series models * Startup experience, comfortable with a small dynamic team. * Location wise, strong preference for in-person in Waterloo or San Francisco however remote work is possible for exceptional candidates.

TIDAL was founded for artists by artists as the next innovative streaming platform to bring value back to the music industry. We empower artists with the products, resources, services, and content required to take control of their careers and connect more deeply with fans. Available in over 60+ countries, TIDAL continues to help artists break down economic barriers to continue creating what's next in culture. TIDAL is part of Block, Inc. (NYSE: SQ), a global technology company with a focus on financial services. The Product AI team uses AI/ML to directly support Tidal's mission to be the first consideration for an artist when they want to share their music. On the listener side, we algorithmically surface music artists have shared by creating playlists, making recommendations, and supporting advanced search. We collaborate closely with Design, Business and engineering teams across TIDAL and the rest of Block. We use a wide range of models including simple heuristics, embeddings, deep learning and large-language models. • Develop new AI/ML systems that power Tidal's homepage including search, recommendations, UX and playlists, • Build production systems that personalize the listener's experience, • Be a technical leader and establish quality practices that stick, make broader design decisions and set an example for others to follow, • Collaborate with a cross functional team of designers, business partners, and software engineers to build new technologies and features, • Design experiments, test them on production users, analyze and repeat, • 8+ years building and operating quality software 5+ years of experience with recommender systems, ranking systems, or similar, • Led the development of complex models trained on large datasets powering customer facing features, • Strong software engineering skills Strong communication skills and customer empathy, • Experience with PyTorch, PySpark, Databricks and AWS is a plus We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our ___. While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.

SpaceX is an Equal Opportunity Employer; employment with SpaceX 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 id

Orchard Robotics is a Series A startup backed by top VCs like Quiet Capital, Shine Capital, and General Catalyst. We're securing America’s food supply by building the AI farmer that automates our nation’s farms. We've raised over $25M in pursuit of our mission to help farmers farm more profitably and sustainably than ever before. We start by collecting the most valuable data for farmers, telling them everything about what is growing on their millions of trees, across thousands of acres of farmland. We do this using advanced camera systems we build, that take pictures of every one of the billions of fruit in a farm. This data lives in our cloud data platform, FruitScope, that we've developed from the ground up to help farmers manage their crops with precision. Farmers across the nation use our industry-leading software to look at their data, make critical decisions, and command farming operations on a daily basis. Our technology is used today across some of the largest farms in the nation. In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing. We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems. About the role: * As an early engineer, you'll receive generous equity compensation * Full-time role at our San Francisco, CA office * Flexible working hours * Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium * We move fast, and sometimes this means staying late or working weekends * Our team is close-knit & highly driven, you’ll work directly with our CEO and entire team * We’re deeply motivated by the impact we’re making – every line of code written or new system built means less food that goes to waste, and more people who are fed. What you’ll do: * Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms. * Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems. * Develop, deploy, and monitor infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices. * Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance. * Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems. * Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features. * Be a generalist, supporting different parts of our software stack as needed. What makes you a good fit: * 3-5+ years of experience building production-grade data pipelines and ML infrastructure. * Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). * Strong experience with data engineering tools (e.g., Pandas, SQL, Apache Airflow, Spark). * Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). * Experience working with massive amounts of real-world training data. * Familiarity with MLops software and data engineering to ensure consistent deployment of ML models. * Ability to work independently, learn quickly, and operate in a dynamic environment * Enthusiasm for taking on multiple roles and responsibilities as our company grows. Bonus Points: * Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson * Experience prototyping, evaluating, or deploying new ML/CV models on the edge. If you're looking to help make a positive impact in the world by building the future of farming, come join us!

About the Institute of Foundation ModelsWe are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers. The RoleAs a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world challenges, pushing the boundaries of artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide. • Collaborate with Research teams to understand technologies, adapting and integrating them into codebase., • Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models., • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies., • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency)., • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback., • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality., • Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation., • Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives., • Minimum: Bachelor’s degree or equivalent practical experience., • Preferred: Master's degree or PhD in Computer Science or related technical field., • 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision., • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting., • 2 years of experience with data structures or algorithms in either an academic or industry setting., • 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing., • Excellent problem-solving and troubleshooting skills to address complex technical challenges., • Effective communication and collaboration skills to work with cross functional teams., • 2 years of experience with improving performance during large scale data processing, • Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).

At Reinforce Labs, we partner directly with customers to build AI systems that enhance the safety and reliability of their complex, high-impact applications. In this role, you'll engage directly with clients to deeply understand their specific challenges, conduct thorough data analysis, and deliver trust and safety AI solutions. You'll implement advanced machine learning techniques including LLMs, reinforcement learning, and deep learning - often translating cutting-edge research papers into practical applications. This position combines technical depth with significant client-facing responsibilities. You'll tackle high-stakes problems with unclear solutions but real-world consequences. Key responsibilities include: * Conducting technical research with customers to map critical workflows and developing sophisticated AI probes that identify potential edge-case failures * Performing comprehensive data analysis to build specialized classifiers that detect subtle risks, violations, and anomalies * Implementing and fine-tuning generative models that can simulate rare or high-risk scenarios * Designing systems that enhance human decision-making under pressure Our success is measured by real-world impact. You'll develop and ship solutions that protect people and platforms at scale while building trusted relationships with the clients who depend on our technology. * Experience with ML and deep learning frameworks such as PyTorch or TensorFlow * Ability to translate cutting-edge research papers into practical AI applications * Strong analytical skills to identify trust and safety threat patterns and challenges * Hands-on experience training and deploying machine learning models in production * Proficiency in Python * Experience partnering with trust & safety leads and background in trust & safety, moderation, AI safety, or security-focused ML to deliver state-of-the-art solutions [a big plus] * An advanced degree in computer science or a related field * Experience in early-stage startups * Experience in customer-facing AI technical solutions * Contributions to high value AI/ML community projects Reinforce Labs is a small team with a clear mission: to use AI to make critical systems safer, not just smarter. We value: * Willingness to learn new things, take on diverse tasks, and challenge yourself * Hands-on technical excellence * Ownership * Ability to handle ambiguity * Fast, results-driven delivery

About favorited At favorited, we believe that digital communities should be more than just spaces to watch content. Our platform is a place to connect, engage, and play, and empowers creators by enhancing audience participation and fostering deeper connections. Our work culture is intense and isn’t for everyone. But, if you’re a self-starter eager to shape the future of social interaction with a team that holds itself to the highest standards, this is the place for you. We value open, yet respectful communication and real-time feedback to help each other grow quickly. If you’re passionate about gaming and have a knack for gamifying everyday life, you’ll thrive in our fast-moving, collaborative environment. About the Role We are seeking a Senior DevOps Engineer to build and scale the infrastructure powering favorited’s live-streaming and social engagement platform. You will be responsible for ensuring high availability, reliability, and performance of systems that support millions of users in real time. This role is ideal for someone who thrives in high-pressure, fast-paced environments, loves solving complex infrastructure challenges, and has a passion for designing resilient, automated systems that empower engineering teams to deliver quickly and confidently. We’re looking for someone who is passionate about gaming and excited to deliver new content to users. Responsibilities * Architect, implement, and manage scalable cloud infrastructure on Google Cloud Platform (GCP). * Build and maintain CI/CD pipelines to accelerate software delivery and reduce deployment risk. * Design monitoring, logging, and alerting systems to ensure reliability and fast incident response. * Optimize infrastructure for performance, cost efficiency, and scalability. * Manage containerized workloads with Kubernetes, Docker, and related orchestration tools. * Collaborate with backend, frontend, and mobile teams to support smooth product releases. * Implement and maintain security best practices across infrastructure and deployment pipelines. * Participate in on-call rotations, incident response, and postmortems to continuously improve system resilience. * Stay current with DevOps tools and practices, bringing innovative solutions to the team. What We're Looking For * 7+ years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering. * Strong expertise with Google Cloud Platform (Cloud Run, Cloud Functions, Pub/Sub, Spanner, BigQuery, etc.). * Deep experience with Kubernetes, Docker, and container orchestration. * Proficiency with CI/CD pipelines and automation tools. * Experience supporting real-time streaming, gaming, or large-scale consumer applications. * Hands-on experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK). * Strong scripting/programming skills in languages such as Python, Go, or TypeScript. * Excellent collaboration skills and ability to work in cross-functional teams. * Proven ability to design secure, scalable, and highly available infrastructure. Salary & Benefits Compensation: $150k - $200k base salary + options. Benefits Include: * Unlimited PTO & paid company holidays. * 401(k) plan with company matching to invest in your future. * Comprehensive health insurance to support your well-being. * Stipends for learning, fitness, and books. * Competitive salary that values your expertise and contributions. Where You’ll Work: This is a full-time, on-site position in Santa Monica.

Collaborate across engineering, robotics, and mission teams to integrate ML pipelines with onboard autonomy. Collaborate with some of the top engineers in autonomy, AI, and national security. We're looking for an AI Engineer to join the Fury Team with a deep passion for building next-generation auto

David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human—it fits naturally into everyday life. To unlock the full potential of AI, models need more—and better—audio data. That’s where David AI comes in. David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $25M Series A from Tier 1 investors like Jack Altman (Alt Capital), Amplify Partners, First Round Capital, Y Combinator, and more. Our team is sharp, humble, ambitious, and tight-knit. We’re looking for the best research, engineering, product and operations minds to join us on our mission to revolutionize audio AI. As a Founding Audio AI Research Engineer, you will drive our research roadmap—shaping strategy, leading model development, and working closely with customers and internal teams to deliver high-quality data. You will: * Develop and publish benchmarks and research to evaluate audio and speech quality, collaborating with academic and industry partners to advance the field and set new standards. * Work with researchers across leading AI labs and organizations to build out our data roadmap that will enable future speech models and applications. * Collaborate with our product and operations team to design and conduct experiments that collect high-quality audio data to fuel your cutting-edge research. * Set strategic and technical direction around our R&D roadmap based on latest research. * Ph.D. or Master’s degree in Computer Science, Machine Learning, Electrical Engineering, or a related field with a focus on speech or audio. * Experience with training and evaluating generative audio models. * A deep understanding of Digital Signal Processing fundamentals. * A strong research portfolio with publications at top venues. * Collaborative mindset and experience leading research agendas with product and other teams. * Experience in dataset design and conducting empirical analysis of audio data distributions, identifying biases or gaps, and proposing strategies for improved dataset design or collection. * Research-oriented software engineering skills, including fluency with technologies like PyTorch, TensorFlow, Scikit-learn and Pandas. * Leadership experience in a research setting. * Prior startup experience. * Rapid career growth, at one of the fastest growing Series A companies, within a new and booming industry. * Competitive salary and equity package. * Flexible PTO policy. * Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans. * Paid lunch and dinner in the office, every day through DoorDash. * 401k access.

Ability to mentor and influence engineering teams. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus.

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states. The Waymo Mapping team's goal is to build a high resolution map of the world to support safe autonomous driving. We work on creating the map using a combination of automatic and manual techniques and build the infrastructure to store, process, and distribute the map. Our team collaborates with several other Waymo teams that consume map data. In this role, you will: • Build backend infrastructure for storing and processing many forms of map data, • Apply the latest machine learning technology to generate maps from raw data, • Improve our internal tools for viewing and editing maps, • Scale our systems to support mapping the whole world You have: • B.S. in Computer Science or a similar technical field, or equivalent practical experience, • 3-5 years Machine Learning experience (preferably in Mapping), • Hands-on machine learning experience - ideally on image recognition problems., • Willingness to own problems end-to-end and work on various parts of the system, • A passion for good software engineering It's a Bonus if you have: • M.S. or Ph.D in Computer Science or a similar technical field, or equivalent practical experience, • Experience with Tensorflow and/or C++, • Experience with large-scale data processing using frameworks like Google Data Flow or Apache Beam The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range$204,000—$259,000 USD

Console is an AI platform that automates IT and internal support. We help companies scale without scaling headcount, and give employees instant resolution to their issues. Our agents understand the full context of the organization, handle requests end-to-end and pull in humans only when necessary. Today, companies like Ramp, Scale, Webflow, and Flock Safety rely on Console to automate over half of their IT & HR requests. We've won every bake-off against our competitors, closed every trial customer and expect to 10x usage by year-end. We're a small, talent-dense team: naturally curious, high-agency and low-ego. Our organization is very flat and ideas win on merit, not hierarchy. We're hiring exceptional people to keep up with demand. We're backed by Thrive Capital and world-class angels. As an Applied AI Engineer at Console, you’ll work on the core agent loop and the many AI flows that make our product feel like magic. You will work closely with the product team and leadership to ship experiences which delight users and "just work". Some examples of work you might do: * Building a copilot agent that human agents can delegate work to and get 10x more done * Architecting product flows that collect user feedback and feed into online evals for rapid iteration * Learning from unresolved tickets and suggesting new automations to customers automatically You'll have room to be creative, own projects end-to-end, and shape both the platform and the product vision. This role is based in San Francisco, CA. We work in-person and offer relocation assistance to new employees. * You're a product builder with strong generalist technical skills, and you know how to maximize your impact to deliver great experiences for users and customers * You have great taste; you understand that the best AI experiences feel great to use and you care deeply about getting the details right * You carefully study data to discover qualitative insights from individual traces and can build quantitative systems to evaluate performance at scale * You're immersed in the world of frontier AI and constantly learning about effective AI architecture * You've worked on AI systems with real usage and know how to iterate effectively on production agents * 4+ years of full-time software engineering experience, with a recent focus on applied AI product engineering * Comfortable working and contributing across the entire stack (Typescript/Node/React) * Obsessed with building incredible product experiences for users, and never happy with "good enough" * Product-market fit: We have built the leading product in our category, in a massive market. We've hit an inflection point and are on track to build a generational company. * World-class team: We seek high agency contributors who are comfortable navigating ambiguity, ruthlessly prioritize what matters and are action-biased. * Grow with us: We reward impact, not credentials or years of experience. We intend to grow talent from within as we scale up. * Competitive pay and benefits: top compensation with full benefits including: * Equity with early exercise & QSBS eligibility * Comprehensive health, dental, and vision insurance * Unlimited PTO * 401(k) * Meals provided daily in office

Master's degree or PhD in Computer Science, Engineering, or a related technical field. Strong communication skills, a passion to make a business impact, and a drive for engineering excellence. In this hybrid role, you will report to the Engineering Director in Perception.

About Sesame Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice companions part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive. About the Role We are seeking an engineer living at the intersection of embedded systems and ML to enable rich, reliable interactions on wearable devices. The ideal candidate will be comfortable working across the software stack, excited by the idea of taking a feature from the whiteboard to a product in customers’ hands. You’ll work closely with hardware, firmware, and product teams to make the interaction feel effortless and consistent for every user, in every environment. Responsibilities: * Design, train, and deploy algorithms for gesture detection on ultra-low-power embedded hardware. * Evaluate and adapt larger ML models for running on mobile class hardware. * Own the full development cycle: system design, data collection & curation, synthetic data generation, model training & evaluation, and on-device optimization. * Collaborate with electrical, mechanical, and product teams to integrate algorithms with evolving hardware designs. * Pick promising approaches from the literature to bet on, and create new approaches where necessary to achieve our unique goals. Required Qualifications: * 10 years of experience in Software Engineering, ML Research, or related fields. * Experience working with a high degree of autonomy in ambiguous environments. * Proven experience building and deploying ML algorithms on embedded or resource-constrained devices. * Proficiency in Python and C/C++, with experience in frameworks such as PyTorch or TensorFlow. * Hands-on experience with end-to-end ML workflows, from data capture to on-device deployment. * Strong grasp of signal processing and/or time-series analysis for sensor data. * Excellent communication skills and the ability to work collaboratively across disciplines. * Bachelor’s degree or higher in computer science, electrical engineering, machine learning, or related field. Preferred Qualifications: * Master’s / Ph.D. in a relevant field. * Experience with wearables, IMUs, or tactile/force sensors. * Familiarity with synthetic data generation and augmentation techniques. * Experience in a startup or fast-moving product environment. * Experience deploying models in products. * Track record of optimizing algorithms for power, latency, and memory footprint. Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities—contact for assistance. Full-time Employee Benefits: * 401k matching * 100% employer-paid health, vision, and dental benefits * Unlimited PTO and sick time * Flexible spending account matching (medical FSA) Benefits do not apply to contingent/contract workers

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms. In this role, you'll: • Architect, design, and implement compiler support for novel features of our unique neural network inference platform, • Analyze and enhance the behavior of existing compiler features to achieve optimal performance on state-of-the art neural networks, • Work together with model developers and hardware architects to improve the efficiency of inference hardware via software/hardware codesign, • Guide the development of future hardware solutions tailored to meet the needs of Waymo’s unique machine learning requirements At a minimum we’d like you to have: • BS degree in Computer Science/Electrical Engineering or equivalent practical experience, • 3+ years of industry experience, • Experience with compilers and parallel computing, • Strong C++ and/or Python programming skills It's preferred if you have: • Experience with domain-specific compilers, especially with neural networks, • Knowledge of computer architectures used for neural network inference, and neural network performance characteristics, • Knowledge of the principles behind popular machine learning and neural network algorithms and applications The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range$170,000—$216,000 USD

Axiado is an AI-enhanced security processor company redefining the control and management of every digital system. The company was founded in 2017, and currently has 100+ employees. At Axiado, developing great technology takes more than talent: it takes amazing people who understand collaboration, respect each other, and go the extra mile to achieve exceptional results. It takes people who have the passion and desire to disrupt the status quo, deliver innovation, and change the world. If you have this type of passion, we invite you to apply for this job. We are on the lookout for a Machine Learning Engineer with a specialized focus on cybersecurity. The candidate should have a comprehensive understanding of the evolving landscape of cyber threats and be equipped with the skills to develop AI-driven solutions to these challenges. This role demands expertise in handling and mitigating sophisticated cyber-attacks such as ransomware, as well as ensuring high-level security in data centers and operational environments. Key Responsibilities: 1. End 2 End Machine Learning Pipeline Development: · Design and manage end-to-end machine learning pipelines tailored for cybersecurity applications. · Implement effective data preprocessing and feature engineering strategies specific to cyber threat detection. 2. Expertise in LLMs, Transformers, and Frameworks: · Utilize large language models and transformers to analyze and predict cybersecurity threats. · Proficient in frameworks like PyTorch and TensorFlow, applied in the context of cybersecurity. 3. Specialized in Cyber Threat Detection and Mitigation: · Develop AI-based solutions for the detection and prevention of ransomware and other advanced cyber threats. · Implement BMC (Baseboard Management Controller) level security measures for data center protection. · Conduct machine learning-based behavioral analysis for routine operational environments to detect anomalies and prevent intrusion. 4. Edge Computing for Cybersecurity Applications: · Optimize cybersecurity-focused machine learning models for deployment on edge devices. · Address the unique challenges of implementing AI solutions in resource-constrained environments. 5. Professional and Research Expertise in Cybersecurity and AI: · Prefer candidates with experience in cybersecurity and AI, with the ability to turn research into practical solutions. · Actively engaging in research, staying abreast of the latest threats and technological advancements in cybersecurity. · 5+ years of experience in machine learning and cybersecurity. · Bachelor's or Master’s degree in Computer Science, Cybersecurity, Engineering, or a related field with a focus on AI/ML. · Strong programming skills in Python, with experience in relevant ML libraries and frameworks. · Demonstrated ability to solve complex problems and a commitment to innovation in the field of cybersecurity. · Excellent communication skills and the ability to work collaboratively in a team environment. Axiado is committed to attracting, developing, and retaining the highest caliber talent in a diverse and multifaceted environment. We are headquartered in the heart of Silicon Valley, with access to the world's leading research, technology and talent. We are building an exceptional team to secure every node on the internet. For us, solving real-world problems takes precedence over purely theoretical problems. As a result, we prefer individuals with persistence, intelligence and high curiosity over pedigree alone. Working hard and smart, continuous learning and mutual support are all part of who we are. Axiado is an Equal Opportunity Employer. Axiado does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

Infrastructure Engineer - Site Reliability. Collaborating closely with ML engineers, DevOps, and infra teams to improve system reliability and performance. Familiarity with software release engineering with for ML/AI systems is a plus.

SketchPro is building the first AI junior architect. We integrate deeply into architectural workflows and standards, helping firms move faster and smarter. We’ve successfully launched our AI rendering product to top global firms. Now, we’re embedding AI directly into Autodesk Revit, the industry standard for architectural documentation, with SketchPro Copilot enabling AI agents to draft, generate, and automate the grunt work of architecture. We’re a team of AI engineers and seasoned architects, bridging domain expertise with frontier technology. We’re looking for a founding AI engineer to apply SOTA LLMs and VLMs to build agentic workflows for 3D CAD and documentation. This role will sit at the intersection of cutting-edge ML research and real-world AEC workflows, applying frontier LLMs to real customer problems. This role is fully in-person 5x/week at our SF office next to Salesforce Tower. • Build agentic architecture using LLMs and VLMs to reason over 2D + 3D data, • Build real-world integrations into industry platforms like Autodesk Revit, Bluebeam, Procore, and more, • Collaborate with architects, engineers, and product teams to deeply understand CAD workflows and translate them into AI-first systems., • Prototype and iterate rapidly on LLMS for geometry generation, drafting, and construction documentation., • Strong product/engineering background building products with AI at their core, • Demonstrated ability to take ambiguous problems and craft reliable and efficient solutions., • Shape the future of how buildings get designed and built., • Work on frontier AI problems applied to a $100B market that is overlooked by Silicon Valley, • Join a fast-growing, venture-backed team supported by Khosla Ventures, Neo, and top leaders from OpenAI, Ramp, Harvey, Brex, and more., • Competitive compensation ($160k-225k+ salary + 1-3% founding equity), • Medical, Dental, Vision coverage, • Expensed lunch and dinner 5x/week in SF office, • Health + Wellness Stipend

A strong background in Linux systems architecture and engineering.

At Sable, we’re building digital-human enterprise workers for the world’s largest companies. We’re redefining the future of work by combining voice, video, and browser navigation with deep business context to create the first truly multimodal digital-human workers. With strong market demand and an aggressive six-month product roadmap, we’re expanding our team. We’re hiring across multiple roles at our San Francisco headquarters to help shape the product that will define the future of GTM.

At 42dot, our Senior Machine Learning Engineers conduct research and development on machine learning algorithms to ensure safe autonomous driving. Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field relevant to machine learning, or equivalent experience.

About Arc Institute The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley. While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include: • Funding: Arc will fully fund Core Investigators’ (PIs’) research groups, liberating scientists from the typical constraints of project-based external grants., • Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators., • Support: Arc aims to provide first-class support—operationally, financially and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction., • Culture: We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration. Arc has scaled to nearly 200 people. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years. About the position We are searching for an experienced and collaborative machine learning research engineer focused on advancing the frontiers of biological foundation models. This role will contribute to the development and application of Arc’s Virtual Cell Initiative (), and other projects in the context of Institute-wide machine learning efforts. About you • You are an innovative machine learning engineer with a deep understanding of ML principles, enabling you to design, modify, and critically evaluate model architectures, not just apply existing ones. You have significant experience in training large deep learning models., • You enjoy thinking from first principles, seeking to deeply understand the data and its underlying dynamics to drive effective and innovative modeling strategies., • You are excited about working closely with a multidisciplinary team of computational and experimental biologists at Arc to achieve breakthrough capabilities in biological prediction and design tasks., • You are a strong communicator, capable of translating complex technical concepts to researchers outside of your domain., • You are a continuous learner and are enthusiastic about developing and evaluating a model that impacts many biological disciplines. In this position, you will • Actively participate in the design, implementation, and refinement of state-of-the-art foundation models developed in collaboration with other ML researchers and scientists at Arc with the goal of understanding and designing complex biological systems., • Engineer large-scale distributed model pretraining and pipelines for efficient model inference., • Enable robust systematic evaluation of trained models., • Stay up-to-date with the latest advancements in technologies for large-scale sequence modeling and alignment, and implement the most promising strategies to ensure the underlying models remain state-of-the-art., • Work with experimental biologists to ensure that the developed models are grounded in biologically meaningful problems and evaluations., • Publish findings through journal publications, white papers, and presentations (both internal to Arc and external)., • Foster internal and external collaborations centered on generative design of biological systems at Arc Institute., • Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. Job Requirements • B.S, MS or PhD in Computer Science, Machine Learning or a related field., • Minimum of 5-8+ years of relevant experience in machine learning research or ML engineering in an academic (e.g., PhD) or industry research lab., • Well-versed in machine learning frameworks such as PyTorch or JAX., • Experience with developing distributed training tools such as FSDP, DeepSpeed, or Megatron-LM., • Excellent communication skills, both written and verbal, with a strong track record of presentations and publications., • Ability to communicate and collaborate successfully with biologists and software/infrastructure engineers., • Motivated to work in a fast-paced, ambitious, multi-disciplinary, and highly collaborative research environment. The base salary range for this position is $168,000-$242,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Eudia: Eudia is redefining the future of legal work with AI-powered Augmented Intelligence, enabling Fortune 500 legal teams to move faster, manage risk more effectively, and unlock new business value. Backed by $105M in Series A funding led by General Catalyst, we’re building a category-defining platform that blends AI-driven automation with human expertise, transforming legal from a cost center into a strategic growth driver. At Eudia, we move fast. Unlike traditional enterprise software, our teams ship solutions in days, not months—delivering real impact for some of the world’s largest companies, including Cargill, Coherent, DHL, and Duracell. We’re solving one of the most complex, unsolved challenges in AI: bringing trust, accuracy, and security to legal automation. We’re a team of builders, operators, and problem-solvers who are passionate about reshaping an industry that has long been resistant to change. If you’re looking for a place where you’ll be challenged, take ownership from day one, and work alongside some of the brightest minds in AI and legal —we’d love to meet you. About the Role: As an Augmented AI Engineer, you will work hands-on with clients to deploy, optimize, and scale AI-powered solutions that address mission-critical problems. Combining expertise in AI engineering with exceptional problem-solving and client-facing skills, you will bridge the gap between our cutting-edge AI technologies and real-world applications. This role demands technical proficiency in machine learning, adaptability, and a passion for delivering impactful AI solutions in dynamic environments. Key Responsibilities: • AI Solution Deployment: Deploy, configure, and fine-tune AI models, algorithms, and platforms to meet client-specific use cases, ensuring seamless integration with existing systems., • Model Development & Optimization: Build, train, and optimize machine learning models (e.g., LLMs, computer vision, predictive analytics) tailored to client data and goals., • Data Pipeline Engineering: Design and implement robust data pipelines to process and transform structured and unstructured data for AI model training and inference., • Technical Problem-Solving: Diagnose and resolve complex AI-related issues, such as model performance bottlenecks or data quality challenges, often under tight deadlines., • Client Collaboration: Partner with clients to understand their business objectives, data challenges, and operational needs. Translate these into AI-driven technical requirements., • Feedback Loop: Collaborate with internal AI research and engineering teams to relay client feedback, driving improvements to models and platforms., • AI Innovation:Identify opportunities to enhance client outcomes through advanced AI techniques, such as reinforcement learning, generative AI, or real-time inference. Qualifications: • Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field., • Technical Skills:, • Proficiency in Python and AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)., • Experience with large language models (LLMs), computer vision, or other advanced AI techniques., • Strong knowledge of data engineering (SQL/NoSQL, ETL pipelines, data lakes)., • Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools (e.g., Kubeflow, MLflow)., • Experience with APIs, microservices, and deploying AI models at scale., • Problem-Solving: Ability to tackle ambiguous AI challenges and deliver practical, high-impact solutions., • Communication: Exceptional ability to explain complex AI concepts and model outputs to non-technical stakeholders., • Adaptability: Thrives in fast-paced, client-facing environments with evolving requirements., • Travel: Willingness to travel to client sites as needed (up to 20% of the time, depending on role requirements)., • Experience: 4+ years in AI engineering, machine learning, or client-facing technical roles. Experience deploying AI solutions in production is a plus. Preferred Qualifications: • Experience in industries like healthcare, finance, defense, or logistics, where AI drives decision-making., • Familiarity with generative AI, reinforcement learning, or real-time AI inference systems., • Prior experience in consulting or deploying AI solutions in a SaaS/enterprise environment., • Knowledge of DevOps practices for AI (e.g., CI/CD for ML models, containerization with Docker/Kubernetes). Why You’ll Love Working Here: • Impactful Work: Be part of a team that’s at the forefront of AI innovation., • Growth Opportunities: Work in an environment that encourages professional growth and the exploration of new ideas., • Dynamic Culture: Join a group of passionate, driven individuals who are committed to making a difference. If you’re ready to take on the challenge and make an impact in a rapidly evolving industry, we want to hear from you! -- Compensation Range: $130,000 - $200,000 The posted salary range is based on our research for companies of our stage and size while in compliance with California law. This is a base salary compensation range and we encourage those who are interested to apply and have an initial discussion.

Site Reliability Engineering or similar roles (DevOps, Systems Engineering, Infrastructure Engineering). Join our Site Reliability Engineering team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Site Reliabi

Infrastructure Engineer – Security. This is a hands-on engineering role — you’ll design, implement, and automate secure systems across our platform, working closely with backend and DevOps teams to ensure that security is built into everything we deploy. Collaborate with engineering to embed s

Umbra is an American space technology company delivering advanced systems, from sensors to spacecraft, that empower customers worldwide with unmatched access to critical information from space. Our mission is simple and ambitious: redefine space—for people, systems, and missions in every domain. Umbra’s ecosystem operates through three business units: Remote Sensing (the data), Space Systems (the components), and Mission Solutions (the platforms).Together, our teams develop capabilities that deliver persistent access, resilient performance, and mission-ready solutions, advancing U.S. space leadership while keeping the world safe and informed. About the Team Space Systems – The Components Space Systems is where Umbra turns hardware and software designs into on-orbit realities; developing, implementing and iterating mission-ready core technology, while simultaneously advancing the next generation of our own satellite constellation. Space Systems is vertically integrated across the satellite architecture, thus the team designs, builds, and tests an array of critical components and subsystems, including power systems, communications, control systems, deployment hardware, avionics, and payloads, as well as the flight software, firmware and digital design solutions to support the entire hardware stack. Our focus is on first principles engineering, and our mandate is simple: it has to work when it counts. Every bolt, board, and binary is proven on our own SAR constellation, ensuring flight-proven reliability where failure is not an option. If you want to work on cutting edge space technology while maintaining the highest standard for innovation and mission ready performance, you belong here at Umbra. About the Job We are seeking a skilled and motivated Hardware Test Infrastructure Engineer to join our dynamic Space Systems team. In this role, you will will be responsible for standing up, maintaining, and integrating the hardware infrastructure that powers our engineering test environments, all while working closely with engineers across disciplines. You’ll collaborate with teams to ensure reliable test systems, seamless integration of third-party equipment, and robust infrastructure documentation and support. This position is based on-site in our Santa Barbara/Goleta, CA office. Key Responsibilities • Stand up and maintain servers, computers, and other hardware test resources., • Install and integrate third-party test systems such as thermal chambers, vacuum chambers, and power supplies., • Develop and maintain documentation to support test infrastructure and ensure repeatability., • Troubleshoot hardware issues in partnership with engineers., • Ensure high availability and reliability of test systems and related equipment., • Collaborate with engineers to design, integrate, and operate test infrastructure for Umbra internally developed hardware, such as radios, avionics, GNC peripherals and other subsystems including FlatSats., • Contribute to test readiness and operational success by maintaining hardware performance, reliability, and documentation., • Occasionally support mission-critical activities such as launch and test campaigns outside of standard hours (evenings, weekends)., • Bachelor’s degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience., • 3-5+ years of professional experience in hardware-focused engineering roles., • Proven experience with installation, configuration, and maintenance of servers, computers, and test hardware., • Hands-on experience integrating third-party test systems (thermal, vacuum, power supplies, etc.)., • Strong knowledge of power and networking infrastructure, including harnessing design and maintenance., • Ability to document infrastructure and processes clearly and concisely., • Strong troubleshooting skills with the ability to support engineers across multiple domains. Desired Qualifications • Bachelor’s degree in Computer Engineering, Electrical Engineering, Mechanical Engineering, or related discipline., • 5+ years of experience supporting, testing, or troubleshooting computer hardware and/or complex electronic assemblies., • Proficiency in reading and interpreting electrical schematics, PCB design documents, and mechanical drawings., • Ability to generate and understand system-level block diagrams for hardware/software integration., • Experience working in aerospace, defense, or other high-reliability hardware environment., • Knowledge of automation tools for test environments., • Comfort working in a fast-paced, multidisciplinary engineering environment., • Flexible Time Off, Sick, Family & Medical Leave, • Medical, Dental, Vision, Life, LTD, STD (employer funded), • Vol Life, Critical Illness, Accidental, Hospital Indemnity, Pet Insurance (employee funded), • 401k with 3% non-elective company contribution, • Stock Options, • Free Parking, • Free lunch in office daily Umbra is an Equal Opportunity Employer. We do not discriminate in hiring on the basis of sex, gender identity, sexual orientation, race, color, religious creed, national origin, physical or mental disability, protected veteran status, or any other characteristic protected by federal, state, or local law. Employment Eligibility Verification In compliance with federal laws, all hired persons will be required to verify their identity and eligibility to work in the United States by completing the required Employment Eligibility Verification Form (I-9 Form) upon hire. ITAR/EAR Requirements This position may include access to technology and/or data that is subject to U.S. export controls pursuant to ITAR and EAR. To comply with federal export controls, all persons hired must be a U.S. citizen, U.S. national, U.S. lawful permanent resident, refugee or asylee as defined by 8 U.S.C. § 1324b(a)(3), or must otherwise be eligible to obtain the required authorizations from the U.S. Department of State and/or U.S. Department of Commerce as applicable. Pay Transparency This job posting may cover multiple career levels. To ensure greater transparency, we provide base salary ranges for all roles, regardless of location. Our standard pay ranges are based on the role’s function and level, benchmarked against similar growth-stage companies. Compensation may vary based on geographical location, as certain regions may have different cost-of-living factors. The final offer will also be influenced by the candidate's skills, responsibilities, and relevant experience. Compensation Range The Compensation Range for this role is $120,000 - $140,000 DOE.

We are seeking Staff level Engineer/TLM to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and

Lead DevOps Engineer - Middleware Reliability Engineering. Join Visa's Middleware Reliability Engineering team to revolutionize how we deliver and maintain Middleware products supporting critical payment systems. As a Lead DevOps Engineer, you'll lead our automation and observability initiatives ens

Site Reliability Engineering or similar roles supporting production environments, with proven ability to mentor and guide technical teams. Harvey uses algorithms with reasoning-adept LLMs that have been customized and developed by our expert team of lawyers, engineers and research scientists. Partne

About Eudia: Eudia is redefining the future of legal work with AI-powered Augmented Intelligence, enabling Fortune 500 legal teams to move faster, manage risk more effectively, and unlock new business value. Backed by $105M in Series A funding led by General Catalyst, we’re building a category-defining platform that blends AI-driven automation with human expertise, transforming legal from a cost center into a strategic growth driver. At Eudia, we move fast. Unlike traditional enterprise software, our teams ship solutions in days, not months—delivering real impact for some of the world’s largest companies, including Cargill, Coherent, DHL, and Duracell. We’re solving one of the most complex, unsolved challenges in AI: bringing trust, accuracy, and security to legal automation. We’re a team of builders, operators, and problem-solvers who are passionate about reshaping an industry that has long been resistant to change. If you’re looking for a place where you’ll be challenged, take ownership from day one, and work alongside some of the brightest minds in AI and legal —we’d love to meet you. About the Role: We are looking to hire a solutions-minded, AI-focused engineer to join our growing team in Palo Alto. In this role, the candidate will seize a unique opportunity to work with data from Fortune 500 companies' legal and risk departments, developing the most secure, enterprise-grade software using the latest in Generative AI. The opportunity to tackle challenges in creating cloud-agnostic solutions, maintaining stringent security and compliance standards, and building scalable, resilient platforms for enterprise applications, data, AI, and search also exist while you will be able to routinely innovate on behalf of our customers, collaborating with the world's top legal and risk experts, as well as preeminent business, technology, AI professionals, and engineers. Key Responsibilities: • Work closely with customers to understand and address their AI/ML challenges, designing and deploying custom solutions that leverage company technologies., • Act as the primary technical contact, providing hands-on support during deployment and ensuring successful integration., • Collaborate with product management and engineering to convey customer feedback, influencing AI/ML product roadmaps., • Lead the deployment of AI/ML solutions, ensuring smooth integration and ongoing optimization., • Provide technical training to clients, identify challenges in AI/ML deployments, and proactively improve model performance., • Maintain clear communication with all stakeholders, providing regular updates on progress and outcomes. Qualifications: • Master’s or Ph.D. in Computer Science, Machine Learning, AI, Mathematics, Statistics, or a related field., • 2-5 years of experience in AI/ML engineering, data science, or a similar role, with a strong background in deploying and integrating AI/ML solutions in real-world environments., • Proficiency in LLMs, RAGs, evaluation techniques, and machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages such as Python., • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and ML services is essential., • Strong problem-solving skills in diagnosing and resolving AI/ML model issues, including model drift, data quality challenges, and performance optimization., • Experience in client-facing roles, with excellent communication and interpersonal skills, and the ability to build strong relationships with customers while guiding them through the AI/ML deployment process., • Familiarity with MLOps practices and tools (e.g., MLflow) and experience in model deployment, monitoring, and continuous integration/continuous deployment (CI/CD) of AI/ML solutions., • A passion for AI/ML technologies and a desire to work on innovative solutions that drive significant impact for customers. Preferred Qualifications: • Familiarity with applying artificial intelligence and machine learning techniques in customer deployments, particularly in areas such as data analysis, predictive modeling, or automation., • A background in deploying and supporting software solutions within legal technology or complex enterprise environments, with an understanding of industry-specific challenges and requirements. Why You’ll Love Working Here: • Impactful Work: Be part of a team that’s at the forefront of AI innovation., • Growth Opportunities: Work in an environment that encourages professional growth and the exploration of new ideas., • Dynamic Culture: Join a group of passionate, driven individuals who are committed to making a difference. If you’re ready to take on the challenge and make an impact in a rapidly evolving industry, we want to hear from you! -- Compensation Range: $130,000 - $220,000 The posted salary range is based on our research for companies of our stage and size while in compliance with California law. This is a base salary compensation range and we encourage those who are interested to apply and have an initial discussion.

Partner with researchers and engineers, communicate crisply, and ship with a high‑ownership mindset.

What We Look for in a Great Engineer.

Lead DevOps Strategy: Define and drive the DevOps roadmap, aligning with business and engineering goals. Mentorship: Provide technical leadership and mentorship to DevOps engineers and other team members. Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Headway’s mission is a big one – to build a new mental health care system everyone can access. We’ve built technology that helps people find great therapists with the first software-enabled national network of providers accepting insurance. 1 in 4 people in the US have a treatable mental health condition, but the majority of providers don’t accept insurance, making therapy too expensive for most people. Headway is building a new mental healthcare system that everyone can access by making it easy for therapists to accept insurance and scale their practice. Headway was founded in 2019. Since then, we’ve grown into a diverse, national network of over 60,000 mental healthcare providers across all 50 states who run their practice on our software and have served over 1 million patients. We’re a Series D company with over $325m in funding from a16z (Andreessen Horowitz), Accel, GV (formerly Google Ventures), Spark Capital, Thrive Capital, Forerunner Ventures and Health Care Service Corporation. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. The Ranking & Relevance team’s mission is to help every patient find the right provider for their needs. We are building the matching system that powers this connection, from search and discovery to ranking and personalization. Our goal is to combine cutting-edge machine learning with a deep understanding of patient and provider experience. We are looking for a Staff Machine Learning Engineer to lead the development of Headway’s ranking and relevance models. You will design and build the systems that decide how patients and providers are matched, using search, recommendation, and personalization to help patients through their care journey. You will set technical direction, build the initial stack, and mentor future ML teammates. At Headway, we have built the largest network of therapists who accept insurance in the country. One of our most important challenges is ensuring that patients find the right therapist for them quickly and effectively. To do this, we are investing deeply in search, ranking, and relevance systems powered by machine learning. As a Staff Machine Learning Engineer on the Patient team, you will focus on: • Matching and ranking: Design and scale ML models that power how patients discover and connect with providers., • Personalization: Use patient signals, provider attributes, and outcomes data to improve matching accuracy., • ML infrastructure: Establish the foundation for experimentation, model training, deployment, and monitoring across Headway., • Mentorship and technical leadership: Guide junior ML engineers and data scientists as the team grows, setting the bar for ML practices at Headway., • Cross-functional impact: Partner with product, engineering, and data science to define success metrics, design A/B experiments, and influence product strategy., • You have 6+ years of experience in applied ML roles, with at least 1 year working on ranking, relevance, search, or recommender systems., • You are fluent in Python and have experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, CatBoost, etc.)., • You have taken ML models from research/prototype to production at scale., • You are comfortable designing and running A/B experiments, and you know how to choose the right offline and online metrics., • You combine product intuition with technical depth. You care about making the patient experience meaningfully better, not just optimizing a model score. Nice to have • Experience with matching systems or personalization., • Familiarity with modern retrieval techniques (vector search, embeddings, semantic search)., • Exposure to ML infrastructure such as feature stores, model monitoring, and retraining pipelines., • Experience with Metaflow, SageMaker, and Outerbounds. After you apply to Headway, here are some details of what to expect during the interview process. • Initial screen: You’ll connect with someone in recruiting so you can learn more about the team, Headway’s mission and exciting growth, and we can get a better idea of your background., • First round: You’ll meet with an engineer on the team to do some live coding and learn more about the engineering team., • Final rounds: You’ll meet several more team members for technical and non-technical interviews and leave with a fuller picture of what it’s like to work at Headway., • References and the offer: Our favorite part of the process. We’ll send over all of the details, including specifics on employee equity, and congratulatory messages from excited future team members. The expected base pay range for this position is $269,790 – $317,400, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for performance-based variable compensation and an equity grant, depending on the position and level. We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential. • Benefits offered include:, • Equity compensation, • Medical, Dental, and Vision coverage, • HSA / FSA, • 401K, • Work-from-Home Stipend, • Therapy Reimbursement, • 16-week parental leave for eligible employees, • Carrot Fertility annual reimbursement and membership, • 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st, • Flexible PTO, • Employee Assistance Program (EAP), • Training and professional development We believe a team's strength is in its people, and we cannot achieve this mission without a team that reflects the diversity of this problem – across race, ethnicity, gender, sexuality, age, national origin, religion, family status, disability, military status, and experience. Headway is committed to the full inclusion of all qualified individuals. As part of this commitment, Headway will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or receive other benefits and privileges of employment, please inform the recruiter when they contact you to schedule your interview. Headway employees work remotely across the US, with the option to work from offices in New York City, San Francisco and Seattle. Headway participates in E-Verify. To learn more, click ___ Headway employees work remotely across the US, with the option to work from offices in New York City, San Francisco and Seattle. Headway participates in E-Verify. To learn more, click

At Protegrity, we lead innovation by using AI and quantum-resistant cryptography to transform data protection across cloud-native, hybrid, on-premises, and open source environments. We leverage advanced cryptographic methods such as tokenization, format-preserving encryption, and quantum-resilient techniques to protect sensitive data. As a global leader in data security, our mission is to ensure that data isn’t just valuable but also usable, trusted, and safe. Protegrity offers the opportunity to work at the intersection of innovation and collaboration, with the ability to make a meaningful impact on the industry while working alongside some of the brightest minds. Together, we are redefining how the world safeguards data, enabling organizations to thrive in a GenAI era where data is the ultimate currency. If you're ready to shape the future of data security, Protegrity is the place for you. Protegrity is looking for a Machine Learning Engineer (PhD Required) Location: Menlo Park, CA (In-office, Mon–Thu) The global data privacy software market is projected to grow from $2.36 billion in 2022 to $25.85 billion by 2029. Join us on this journey and make an impact with one of the top 25 global software providers. We look forward to making our world become a better place with you on our team! About the Role: This role is ideal for PhD graduates in technical, math-heavy fields (Physics, Engineering, Mathematics, Biology) transitioning from academia to industry. You’ll join our GenAI team to secure AI infrastructure and develop agentic security solutions for enterprise-scale deployments. Responsibilities: * Architect and implement GenAI systems using agentic coding IDEs (e.g., GitHub Co-Pilot) * Design and run experiments; analyze and present results. * Conduct literature reviews and deep dives on agentic AI research. * Fine-tune LLMs and embedding models. * Apply traditional ML algorithms to large datasets. * Process legal, compliance, and user documentation datasets. * Contribute to roadmap planning and product evolution. Qualifications: * PhD in a mathematics-heavy technical field. * 3–5 years Python experience. * Strong foundation in ML algorithms and metrics. * Experience with PyTorch, TensorFlow. * Familiarity with data security (encryption, masking, tokenization.) * Curiosity and drive to become a GenAI expert. Why Choose Protegrity: * Become a member of a leading Data Protection, Privacy and Security company during one of the best market opportunities to come along in a generation. * Competitive Compensation/Total Reward Packages that include: * Health Benefits (Health/Dental/Vision) * Paid Time Off (PTO) * 401K * Annual Bonus Incentives * Short and Long Term Disability * Work on global projects with diverse, energetic, team members who respect each other and celebrate differences * Talent First Workforce Should you accept this position, you will be required to consent to and successfully complete a background investigation. This may include, subject to local laws, verification of extended education and additional criminal and civil checks. We offer a competitive salary and comprehensive benefits with generous vacation and holiday time off. All employees are also provided access to ongoing learning & development. Ensuring a diverse and inclusive workplace is our priority. We are committed to an environment of acceptance where you are free to bring your full self to work. All qualified applicants and current employees will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability or veteran status. Please reference Section 12: Supplemental Notice for Job Applicants in our to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Protegrity USA, Inc., or its parent company, subsidiaries or affiliates, and the purposes for which we use such personal information.

About Story Story aims to grow the creativity of the internet. The internet has introduced Story is building the IP infrastructure for the internet era, where creativity and intelligence move at the speed of culture, not contracts. Our mission is to unleash the creativity of the internet by making IP programmable, traceable, and monetizable at scale. In our first chapter, we launched mainnet, secured hundreds of thousands of IPs on-chain, and partnered with global brands, leading AI labs, and millions of creators. Story has already proven itself as real infrastructure for IP. Now, with Chapter 2, we are expanding into the most valuable and underserved category of IP: real-world data for AI. As compute and models become commoditized, the true bottleneck is rights-cleared, specialized data, the critical fuel for the next wave of breakthroughs in robotics, healthcare, and embodied AI. From uncrawlable data powering robotic foundation models, to global IP portfolios, to viral fan-made content, Story unlocks value from assets that were once unreachable. Just as Git transformed open source software, Story is redefining how IP is created, licensed, and monetized for the AI era. Backed by top global investors and led by a team with deep expertise across technology, media, and business, Story is building the licensing infrastructure for the new IP economy, and we are only getting started. The Role We are seeking a highly skilled Infrastructure Engineer to join our fast-growing company. This key engineering role requires a passion for infrastructure automation and operation. You will be responsible for designing, implementing, and maintaining infrastructure frameworks and tools to automate and monitor the infrastructure of our blockchain. You will collaborate closely with developers to create infrastructure solutions that enhance the quality and speed of our software development, deployment processes, as well as monitoring and operating the infrastructure. • Architect, design, implement, and maintain infrastructure frameworks for blockchain networks and backend services., • Collaborate with QA and development teams to identify and fix bugs, performance bottlenecks, and security vulnerabilities., • Design, develop, and document tools and pipelines to support testing, debugging, reporting, and monitoring of blockchain applications, networks, APIs, etc., • Monitor the infrastructure, providing timely responses and escalating issues as needed., • Implement and maintain CI/CD pipelines to streamline the development and deployment process., • Ensure infrastructure security and compliance with industry standards., • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field., • 6+ years of experience in infrastructure automation, preferably in blockchain or distributed systems., • Proficiency with mainstream infrastructure automation tools such as AWS, GCP, Kubernetes, and Docker., • Strong development experience with Terraform, Ansible, Grafana, and Prometheus., • Extensive operational experience and a proactive mindset., • Experience with testing frameworks and tools is a huge plus., • Familiarity with blockchain technology and decentralized application (dApp) development., • Knowledge of additional tools such as Jenkins, GitHub Actions, Elastic Stack (ELK), and Helm is desirable., • Excellent problem-solving skills and the ability to work in a fast-paced environment., • Strong communication skills and the ability to collaborate effectively with cross-functional teams.

The Company Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time. The Role Metropolis is seeking a Senior Machine Learning Software Engineer to accelerate the development of our proprietary computer vision and machine learning software that powers our mobility products. As part of the Metropolis Machine Learning Team, you will be responsible for the development, deployment, and ongoing optimization of edge-deployed software. These systems are foundational to the Metropolis platform and have correspondingly large potential impacts on Metropolis and its customers. You will find this to be a challenging opportunity filled with unique technical and operational considerations while being able to learn from and leverage our existing Computer Vision based development and operational ecosystem. The right candidate will possess a strong background in C++ and OpenCV, experience with computer vision and ML on edge / embedded systems, and demonstrated experience taking complex software systems from concept to production. You can expect to be working on all stages of the software development pipeline – from problem analysis and design to prototyping and deployment. You should be able to thrive and succeed in an entrepreneurial setting, working collaboratively in a fast-paced environment with multiple stakeholders. You won’t be afraid to break new technological ground at Metropolis and are more than willing to roll up your sleeves, dig in and get the job done. Responsibilities • Work with the Machine Learning Team to design, develop, improve, and optimize computer vision, machine learning and application software on edge devices using C++., • Participate in all phases of embedded software development, from concept and design to deployment and maintenance., • Identify top-level software requirements and establish development best practices., • Deliver high-quality C++ code in a real-time embedded environment., • Perform optimization on ML models targeting different hardware accelerators e.g. CUDA cores, Qualcomm DSP, etc., • Implement, manage, and support over-the-air software updates to edge systems., • Communicate ideas and results effectively, verbally and in writing, to a wide range of technical and non-technical audiences. Requirements and Qualifications • BS, MS, or Ph.D. in a Computer Science and Engineering or relevant discipline., • 5+ years experience in modern software design, development, version control, refactoring, and testing, • 5+ years of experience with C++17 onward and a strong understanding of object-oriented programming, • 3+ years of experience working with C++ OpenCV, SQLLite and MQTT., • Experience in parallel computing, accelerator architecture, CUDA, Qualcomm DSP, and TensorRT libraries., • Experience with ARM Cortex series microcontroller, • Excellent written and verbal communication skills with a proven ability to present complex technical information in a clear and concise manner to a variety of audiences, • Previous experience working inside innovative, high-growth environments, • Strong preference for candidates to be local to the Seattle area. Will also consider candidates in Los Angeles, Seattle, and New York. When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 to 200,000.00 annually. The actual base pay offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Hybrid #LI-DL1 #LI-H Join us in making a difference as we build our future. Metropolis is an equal opportunity employer, dedicated to diversity, equality, and inclusion, and provides equal employment opportunities to all employees and applicants for employment. Metropolis 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.

The role We are seeking a Manager, Data Science to join our Lending Business Insights and Data Science team. This leader will partner closely with SoFi’s Product, Engineering, and Finance teams to optimize our application funnels through experimentation, understand product usage across member segments, and enable data driven strategic decision making. The ideal candidate is both forward-thinking and hands-on, has a strong sense of ownership and drive for delivery, and is a good mentor and co-worker. We pride ourselves on a philosophy of continuous learning, and you should likewise be committed to furthering growth and providing mentorship for your team members. What You'll Do • Build and lead a great data science team to deliver the best consumer financial products on the market, • Apply your expertise in quantitative analysis, data science, and the presentation of data to see beyond the numbers and understand how our users interact with our products or SoFi Platforms, • Partner with Business, Product, Engineering, and Finance teams to solve problems and identify trends and opportunities, • Inform, influence, support, and execute our product decisions, • Build/maintain reports, dashboards, and metrics to monitor the performance of our products, • Manage the development of data marts, gather requirements, organize sources, and support product launches while keeping the team accountable and impactful What you’ll need: • Bachelor’s Degree in Computer Science, Math, Physics, Engineering, or related quantitative field., • 2+ years of experience in managing other team members in a formal or informal capacity, • 5+ years of experience doing quantitative analysis at a technology company, consulting, investment banking, or product management including experience with SQL or other programming languages, • 5+ years of experience with applied statistics or experimentation (i.e. A/B testing) in an industry setting, • Experience initiating and drive projects to completion with minimal guidance, • Experience communicating and representing results of analysis to senior leadership, • Understanding of statistical analysis, experience with packages, such as Python, R, • Experience with cloud-based platforms, such as AWS, Snowflake, • Experience with building data visualizations with Tableau, Looker or other BI tools

Perplexity is looking for an Applied ML Engineer to design, build, and iterate on cutting-edge AI models powering our core experience. As an expert in machine learning and artificial intelligence, you will develop scalable and impactful solutions for user personalization, query understanding, and content discovery - fulfilling the curiosity of millions of users across the globe. Key Responsibilities * Apply state-of-the-art ML and LLM techniques to solve problems spanning: * Personalization (LLM memory, context summarization, retrieval and ranking); * Query Understanding (intent modeling, rewriting, agentic decomposition); * Content Discovery (feed ranking and surfacing) * Rigorously evaluate LLM/ML models with both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact. * Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement. * Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements. * Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle. Preferred Qualifications * 5+ years experience building and shipping robust ML/AI models for large-scale, user-facing or data-driven products. * Deep expertise in deep learning (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and/or ranking. * Strong software engineering skills (Python, production-quality codebases, collaborative development). * In-depth experience with the full ML lifecycle: data analysis, feature engineering, iterative model development, rigorous evaluation, and ongoing monitoring/improvement. * Proven collaborator and communicator; excels in high-velocity, cross-functional teams. * Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI. * BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience). Bonus Points For * Experience with LLM prompt engineering, Retrieval-augmented generation (RAG) based systems. * Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc). * Open-source or published contributions in ML, NLP, IR, or relevant research fields.

Lightfield is a new kind of CRM. It's a collaborative system for founders to find, understand, and serve customers faster than anything before it. It captures every customer interaction, generates and performs followup actions, and answers questions about your go-to-market using knowledge obtained in real time. Our system is tuned and customized by a team of experienced sellers, engineers, and researchers. Many of us worked on large-scale products including Llama, Messenger, Instagram, Pinterest, and Linkedin before this. Lightfield's AI/ML team builds the experiences at the core of our product, developing new applications to wow our customers. Today, the team is focused on building a powerful, domain-specific AI that outperforms generic LLMs We’re inspired by the challenge of creating innovative new AI products for people doing serious work, and we’re looking to grow our AI/ML team to meet that challenge. * Lead the development of ML product development infrastructure, focusing on scaling and innovating in areas of collaboration and versioning, particularly in the context of LLM model training and prompting * Create and maintain a platform that will be used by multiple teams working on ML products, ensuring its scalability, efficiency, and user-friendliness. * Collaborate closely with internal teams to integrate ML solutions and define best practices for software engineering in an AI-driven development landscape. * Help build a world-class AI/ML engineering team by recruiting and mentoring teammates * Address and solve open-ended technological challenges in software engineering at scale, especially in the context of AI-driven systems. * You have a BS or MS degree in CS, Engineering, AI or a related field. * 6+ years experience in software engineering with a focus on ML infrastructure. * You have a strong understanding of deep learning AI/ML frameworks or cloud services * Experience with the integration of software engineering with large language models. * Ability to navigate and solve open-ended technological challenges in a fast-evolving AI landscape. * Excellent collaboration skills, with the ability to work effectively with both internal teams and external partners. * Strong problem-solving skills and the ability to handle complex, cross-functional projects. * Publications in applied AI/ML scientific journals * Experience navigating open source/vendor solutions in LLM ops space (LangChain, Llama, Pinecone, etc)

About Checkr Checkr is building the data platform to power safe and fair decisions. Established in 2014, Checkr’s innovative technology and robust data platform help customers assess risk and ensure safety and compliance to build trusted workplaces and communities. Checkr has over 100,000 customers including DoorDash, Coinbase, Lyft, Instacart, and Airtable. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on ___ and is a Y Combinator 2024 ___. About the role: As a Site Reliability Engineer II on the Platform team, you will uncover issues and technical challenges across the engineering teams and platforms, and develop creative solutions to resolve them. You will strive towards the right balance between enforcing standardization and accommodating uniqueness. The person in this role will have a chance to demonstrate a degree of autonomy with their work and help with complex support requests and have an impact across engineering. Who You Are: • You have a strong sense of ownership with a proactive nature, • You are motivated by sharing knowledge and excited by what can be done when a group of people are aligned in their vision, • You possess a great desire to collaborate, improve, and innovate, • You are passionate about observability at scale and finding solutions to issues. What You’ll Do: • Collaborate, drive, and execute architectural discussions with cross-functional teams, • Influence cross team projects and SREs technical roadmap to enable engineering and help Checkr customers, • Design, build, ship, and maintain the core software libraries, tools, and patterns used by all of Checkr’s engineering teams, • Troubleshoot complex production issues across the stack, with respect to performance, availability, and data quality, • Provide consultation and feedback across teams to ensure we are building highly reliable systems, • Present detailed technical information and benefits of the Checkr platform to a wide array of customers, including operations, developers, technical architects, and executives What You Bring: • Degree in Computer Science (or related field), • 3+ years experience as a software engineer (Ruby, Python, or GoLang), • 3+ years experience in maintaining and observing production customer facing environments in AWS or Azure, • 3+ Experience as incident commander or response team member of an outages in production, • Experience with containers and container orchestration, • Understanding of the basic concepts of infrastructure behind a micro-service architecture, REST APIs, and asynchronous queueing models, • Strong collaboration, documentation, communication, and project management skills, • Experience driving platform adoption with various product engineering teams, guided by a self-service and product-first approach, • A passion for customer-centricity and building relationships with other teams, • Unwavering commitment to operational security and best practices What you’ll get • A fast-paced and collaborative environment, • Learning and development allowance, • Competitive cash and equity compensation and opportunity for advancement, • 100% medical, dental, and vision coverage, • Up to $25K reimbursement for fertility, adoption, and parental planning services, • Flexible PTO policy, • Monthly wellness stipend, home office stipend At Checkr, we believe a hybrid work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO, San Francisco, CA, and Santiago, Chile. Individuals are expected to work from the office 2 to 3 days a week. In-office perks are provided, such as lunch four times a week, a commuter stipend, and an abundance of snacks and beverages. One of Checkr’s core values is Transparency. To live by that value, we’ve made the decision to disclose salary ranges in all of our job postings. We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see ___. The base salary range for this role is $135,000 to $159,000 in San Francisco, CA. Equal Employment Opportunities at Checkr Checkr is committed to building the best product and company, which requires hiring talented and qualified individuals with a diverse set of perspectives and lived experiences. Checkr believes in hiring people of all backgrounds, including those whose histories are impacted by the justice system in accordance with local, state, and/or federal laws, including the ___.

Promise is a pioneering film and TV studio at the forefront of the generative AI revolution. Our mission is to reimagine what's possible in entertainment by bringing together the world's most visionary storytellers and GenAI creators, empowered by cutting-edge tools and proprietary workflows. Through bold collaborations and a forward-thinking approach to sourcing IP, we are building a dynamic slate of original and licensed projects that push creative boundaries. Backed by premier VC firms, Promise is shaping a new era in GenAI-powered storytelling, where creativity knows no limits. Promise is building MUSE, the next-generation platform where AI meets VFX to revolutionize how content is created. We're looking for a passionate and talented AI/ML Engineer to join our innovative team and help us push the boundaries of what's possible. We are seeking a results-oriented AI/ML Engineer to develop and deploy machine learning and artificial intelligence models that will directly advance the company’s product roadmap. This critical role involves hands-on development and close collaboration with the Product and Pipeline teams to deliver production-grade AI features and data-driven insights. The ideal candidate thrives on translating creative challenges into scalable technical solutions and is passionate about seeing their work immediately impact the future of film and television production. * Model Development & Deployment * Model Building: Build, evaluate, and deploy Machine Learning (ML) models and complete pipelines for new and existing product features within the MUSE platform. * Research Implementation: Research, select, and implement state-of-the-art ML algorithms and tools best suited to business and creative challenges. * Production Maintenance: Maintain, optimize, and monitor models in production, ensuring high availability, low latency, and required accuracy targets are consistently met. * Collaboration & Strategy * Product Alignment: Work side-by-side with the VP of Product to align development efforts with product requirements and strategic company goals. * Stakeholder Communication: Translate complex ML concepts for cross-functional stakeholders, actively contributing to product planning and requirements definition. * Documentation & Compliance: Document solutions, experiments, and results thoroughly, maintaining traceability and compliance for all models and the pipeline. * Technical Proficiency: Proficiency with Python and standard ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn). * Production Experience: Practical experience deploying ML features and models into production environments. * Collaboration: Track record collaborating closely with product leads or directly within product teams to define and deliver features. * Communication: Strong communication and documentation skills, effective for both highly technical and non-technical creative audiences. * Experience with Generative AI models (e.g., Diffusion Models, Transformers) or computer vision tasks. * Familiarity with MLOps tools for model versioning and monitoring. * A background or strong interest in the film, VFX, or media technology industry. * Core Languages: Python (Expert). * ML Frameworks: PyTorch, TensorFlow, or equivalent. * ML Libraries: Scikit-learn, NumPy, pandas. * Deployment: Experience with API development and packaging models using technologies like Docker. * Cloud & MLOps: Familiarity with cloud services (AWS, GCP, or Azure) and tools for managing the ML lifecycle. We offer a highly competitive compensation package commensurate with experience, including equity. We believe in supporting our team’s well-being and growth. Our comprehensive benefits package includes: * Health & Wellness: Comprehensive medical, dental, and vision insurance coverage, with employee premiums covered 100%. * Time Off: Generous paid time off (PTO) policy, including company holidays and sick leave. * Financial Security: 401(k) matching program to help you plan for your future. * Professional Development: Annual stipend for continuing education, conferences, and technical training. * Work Environment: A dynamic, creative, and inclusive hybrid work environment based out of our innovative studio. Promise is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. About the Role As an AI Engineer & Researcher - Reasoning Post-training at xAI, you will drive the evolution of our AI models' reasoning capabilities through inventive post-training approaches, embracing a broad scope that spans from conceptual exploration to practical implementation. This role demands a blend of technical depth and boundless creativity, where you'll refine pre-trained models to excel in logical inference, multi-step problem-solving, and adaptive thinking—without delving into initial training phases. By devising unconventional techniques and fostering creative breakthroughs, you'll help our AI systems tackle complex, real-world challenges with unprecedented intelligence and reliability, collaborating across teams to turn bold ideas into transformative enhancements. Focus • Post-Training Optimization: Apply and innovate on post-training methods like fine-tuning, reinforcement learning variants, or data augmentation to sharpen reasoning skills, ensuring models deliver more accurate, coherent, and insightful outputs., • Creative Methodology Design: Invent novel strategies for enhancing reasoning, such as custom prompting frameworks, synthetic reasoning datasets, or hybrid techniques that push the limits of model cognition through out-of-the-box thinking., • Problem-Solving Exploration: Tackle broad reasoning challenges creatively, from debugging logical inconsistencies to engineering solutions for edge-case scenarios, using iterative experimentation to uncover hidden potential in models., • Evaluation and Iteration: Develop creative benchmarks and metrics to assess post-training impacts on reasoning, enabling rapid cycles of refinement that align with evolving user needs and technological frontiers., • Collaborative Innovation: Partner with diverse teams to integrate post-training advancements into our AI ecosystem, leveraging your creativity to inspire cross-pollination of ideas and accelerate overall model intelligence. Ideal Experience • Post-Training Specialization: Extensive hands-on experience with post-training techniques (e.g., RLHF, DPO, or alignment methods) focused on reasoning improvements, with a portfolio of successful model enhancements., • Creative Problem-Solving Prowess: Demonstrated ingenuity in solving ambiguous AI challenges, evidenced by innovative projects, research contributions, or unconventional approaches that yielded breakthroughs., • Broad Technical Foundation: Proficiency in AI engineering tools (e.g., Python, PyTorch) and a solid grasp of model architectures, enabling you to navigate wide-ranging tasks from ideation to deployment., • Research Versatility: Background in AI research with emphasis on reasoning, logic, or cognitive science, including publications or experiments that highlight creative applications in post-training contexts., • Adaptable Expertise: 3+ years in multifaceted AI roles at cutting-edge organizations, where you've thrived in broad scopes by balancing creativity with rigorous execution to deliver high-impact results. Location • We hire engineers in Palo Alto. Our team usually works from the office 5 days a week but allow work-from-home days when required. Candidates are expected to be located near Palo Alto or open to relocation. Interview Process After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15-minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews: • Coding assessment in a language of your choice., • 2x post-training technical sessions: These sessions will be testing your ability to formulate, design and solve concrete problems in training data for post-training., • Meet the Team: Present your past exceptional work and your vision with xAI to a small audience. Our goal is to finish the main process within one week. All interviews will be conducted via Google Meet. Annual Salary Range $180,000 - $440,000 USD xAI is an equal opportunity employer.

About Gusto Gusto is a modern, online people platform that helps small businesses take care of their teams. On top of full-service payroll, Gusto offers health insurance, 401(k)s, expert HR, and team management tools. Today, Gusto offices in Denver, San Francisco, and New York serve more than 400,000 businesses nationwide. Our mission is to create a world where work empowers a better life, and it starts right here at Gusto. That’s why we’re committed to building a collaborative and inclusive workplace, both physically and virtually. Learn more about our ___. About the Role: Gusto’s Data team leverages Gusto’s rich dataset to guide product direction and decision-making by building the right AI/ML solutions at scale. For this role, we are looking for a technical leader (an individual contributor) to drive the scale and optimization of our customer experience and customer journey via building AI and ML enabled experiences and services. In this role you will build and optimize AI/ML solutions and infrastructure that power our customer journey related products. You’ll be working with a strong AI/ML team and seasoned leaders in Engineering, Product, Design, Data Science, Marketing, and Sales. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the unified service platform stack using machine learning and AI to personalize world class content for our customers and enhance customer experience. Here’s what you’ll do day-to-day: • Design and develop scalable, production-grade AI and machine learning models for complex business problems., • Lead and mentor teams of ML scientists and engineers, fostering a culture of technical excellence and innovation., • Collaborate cross-functionally with product, engineering, and business stakeholders to identify AI opportunities and translate them into actionable solutions., • Stay current with latest AI research; prototype and implement new algorithms and advancements from academia and industry., • Oversee model validation, deployment, and lifecycle management, ensuring robust monitoring, explainability, and performance., • Guide technical strategy, roadmap, and architectural decisions for the ML/AI function., • Communicate findings, roadmaps, and performance results clearly to executives and non-technical partners. Here’s what we're looking for: • 8+ years’ hands-on experience building and deploying end-to-end ML/AI systems in industry or academia., • Deep expertise in advanced ML methods (supervised, unsupervised, reinforcement learning, deep learning, NLP, etc.)., • Proven track record of delivering large, impactful ML projects into production environments., • Proficient in modern ML frameworks (TensorFlow, PyTorch, etc.) and cloud computing platforms (AWS, GCP, or Azure)., • Strong programming skills in Python and familiarity with best engineering practices (CI/CD, testing, code review)., • Demonstrated leadership in cross-disciplinary teams and ability to mentor scientists and engineers., • Excellent communication skills and business acumen., • Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field is a plus. Our cash compensation amount for this role is targeted at $200k-245k in Denver, and $240k-290k for San Francisco, New York, and Seattle and 220k-270k CAD for Toronto. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out ___ and a member of our team will get in touch with you. Gusto takes security and protection of your personal information very seriously. Please review our ___. Personal information collected and processed as part of your Gusto application will be subject to ___.

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Data Foundation & AI team builds advanced ML/AI models and applications that enable product teams to deliver intelligence at scale. We design infrastructure and abstractions that make AI development faster, more reliable, and more impactful. From embeddings and representation learning to applied AI systems, our work provides the building blocks for the next generation of financial services on Plaid. You’ll be a senior machine learning engineer on the Data Foundation & AI team. In this role, you will design, build, and scale advanced ML/AI systems that power Plaid products and applications. Your work may span developing reliable distributed training and serving systems, improving ML operations at scale, and building AI-powered applications that enable new product experiences. • Building and scaling advanced ML/AI systems that power core Plaid products and applications used by millions of consumers., • Driving impact at scale by improving distributed training, serving, and ML operations to make Plaid’s AI capabilities faster, more reliable, and more widely available., • Developing new AI applications that enable innovative product experiences across fintech., • Tackling 0 to 1 problems where you explore new approaches, as well as scaling 1 to 10 systems for reliability and efficiency., • Collaborating with some of the strongest MLEs at Plaid in a high-ownership, bottom-up driven team., • Experimenting with cutting-edge ML and AI techniques while balancing practical productionization and measurable business impact., • 5+ years of experience training, deploying, and scaling ML/AI models in production environments., • Strong experience with distributed systems and ML operations — from large-scale training to low-latency serving and monitoring., • Proficiency in Python and modern ML frameworks (e.g., PyTorch), with the ability to implement and optimize complex models., • Hands-on experience building or scaling ML/AI infrastructure, pipelines, or reusable platforms that support multiple teams., • Curiosity and drive to experiment with advanced AI techniques (e.g., embeddings, retrieval, generative modeling) while staying grounded in production impact., • Experience applying ML/AI in fintech or similarly regulated industries is a plus.