Representative Jobs

About the Team Our DD Labs team builds real-time autonomous delivery systems. The Planning & Decision-Making group is investing heavily in deep reinforcement learning to move beyond classical planning, learning policies that generalize across novel driving scenarios, handle long-tail edge cases, and improve continuously from large-scale fleet data. Our models jointly handle prediction and planning in a single unified architecture. Our stack is pure JAX end-to-end: the same code you train with is the code that runs on the robot. No C++ rewrites, no TensorRT export. A new policy goes from training to on-vehicle deployment in minutes. About the Role As a Senior/Staff Deep RL Engineer, you will design, train, and deploy deep reinforcement learning policies that make real-time driving decisions for our autonomous vehicles. You will own the full lifecycle, from problem formulation and reward design through large-scale distributed training to on-vehicle inference. You'll help define how learned components compose with the rest of the autonomy stack to produce robust, shippable behavior. You’re excited about this opportunity because you will… Formulate complex driving tasks as RL problems with well-shaped reward functions and expressive state/action representations. Design and train model-based deep RL agents using GPU-accelerated simulation at massive scale, including improving the simulator itself. Build and maintain distributed training infrastructure in JAX across large compute clusters. Build agentic optimization systems that automatically improve code, run experiments, analyze metrics, and iterate on RL policies with minimal human intervention. We’re excited about you because… BS/MS/PhD in CS, EE, Robotics, or a related field, with a strong foundation in reinforcement learning and deep learning. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing,

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Pinterest Labs group is dedicated to the development and research of applied machine learning. Our initiatives span a diverse range of AI/ML fields, including fundamental computer vision, multimodal large language models, multimodal representation learning, generative modeling, heterogeneous graph neural networks, and recommender systems. By building foundation ML models that utilize our extensive knowledge graph and billions of Pins, we aim to significantly enhance the core Pinterest product. Our visual modeling team is currently seeking new members to focus on the advancement of vision-centric LLMs. We are building VLMs capable of perceiving intricate visual details and understanding user aesthetics to facilitate communication through visual assets using tools like multimodal search and text-to-image models. This role offers the opportunit

Legal Services NYC (LSNYC) fights poverty and seeks racial, social and economic justice for low-income New Yorkers. For over 50 years, we have challenged systemic injustices that trap people in poverty and provided legal services that help our clients meet basic needs for housing, income and economic security, family and immigration stability, education, and health care. LSNYC is the largest civil legal services provider in the country; our staff of more than 600 people in neighborhood-based offices and outreach sites across all five boroughs helps hundreds of thousands of New Yorkers annually. We partner with scores of community-based and client-run organizations, elected officials, public agencies, pro bono lawyers, and the courts to maximize our effectiveness. Our work fights discrimination and helps to achieve equity for all low-income New Yorkers. LSNYC employees have numerous opportunities for growth and professional development, including access to our internal Justice Learning Center, which provides opportunities to earn free CLEs and gain experience as a trainer. STAFF ATTORNEY – HOMEOWNER DEFENSE PROJECT STATEN ISLAND LEGAL SERVICES Staten Island Legal Services ( across the street from the ferry ), is seeking a full-time Staff Attorney to join our homeowner defense/foreclosure prevention practice. Program Description Staten Island Legal Services (SILS) fights poverty and seeks racial, social, and economic justice for low-income New Yorkers. SILS provides high-quality, innovative representation to address the pressing legal needs of Staten Island’s diverse low-income populations. SILS focuses on the problems that have the greatest impact on our clients — preserving affordable and decent housing, preventing foreclosures, representing survivors of domestic violence, assisting in obtaining government benefits, obtaining immigration status and preventing deportations, and advocating for the LGBTQ community, students with educational needs and

What we’re doing isn’t easy, but nothing worth doing ever is. We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots. As an ML Engineer, Manipulation, you will develop and deploy learning-based manipulation systems that enable mobile robots to interact reliably with the physical world in dynamic human environments. You’ll build perception-to-action models, training datasets, evaluation tooling, and deployment pipelines that improve robustness, generalization, and safety for real-world manipulation tasks at scale. Your work will directly impact the robot’s ability to perform complex interactions consistently across real sites with minimal special-case engineering. Responsibilities Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments). Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training. Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments. Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing. Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware. Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots. Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining. Basic Qualifications Bachelor’s or Master’s degree in Robotics, Computer Scienc

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We’re a team applying ML to push autonomy performance forward. As a Perception ML Engineer, you’ll develop and improve perception models, with ownership of modeling, training, and evaluation. Your work will directly impact how autonomous systems understand rare scenarios, adapt to global geographies, and scale safely. Design and advance perception models that: Improve scene understanding from real sensor data, including 3D and spatial representations Generalize across sensor platforms, geographies, and rare driving scenarios Meet requirements for model quality and onboard inference runtime Tailor Your Impact: Applied ML Depth: Own model architecture, loss design, training, and experiments that deliver measurable perception improvements. Collaborative Delivery: Partner with ML Data Infrastructure and autonomy engineers, contributing across the stack when needed while keeping primary ownership in modeling. About the work You’ll so

Location: Remote with ~40% domestic and international travel Shape the future of cancer care as a Medical Director, Skin/IO at Natera. In this strategic leadership role, you will provide medical expertise and scientific leadership across Natera’s oncology portfolio, with a focus on melanoma, cutaneous malignancies, and immunotherapy applications across solid tumors. You will collaborate with cross-functional teams in research, development, medical affairs, and commercial functions to ensure the scientific integrity and clinical adoption of Natera’s oncology testing solutions. Primary Responsibilities: Clinical Adoption: Lead the clinical strategy and evidence generation for melanoma, non-melanoma skin cancers, and pan-tumor immunotherapy indications. Partner closely with clinical development, medical affairs, and commercial teams to translate emerging evidence into meaningful clinical practice applications. Collaborate with key opinion leaders (KOLs), cooperative groups, and academic investigators to validate and expand clinical use cases for ctDNA-based diagnostics in immuno-oncology. Provide field-facing education and strategic guidance to healthcare providers, payers, and advocacy organizations on clinical utility, interpretation, and impact of MRD and response monitoring in immune-treated populations. Identify and address barriers to adoption by aligning evidence generation, messaging, and stakeholder engagement with evolving standards of care and health system needs. Medical Education and Communication: Serve as the medical and scientific spokesperson for skin and immuno-oncology programs, communicating clinical utility, study data, and product value to external experts and stakeholders. Partner with commercial teams to develop educational resources, medical content, and scientific training for healthcare providers and internal teams. Provide scientific leadership during advisory boards, symposia, and investigator meetings. Representation and Advocacy: Re

Job Description - Data Analyst Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… 1. What you will be doing? As a Data Analyst, your key responsibilities revolve around utilizing Python and SQL for data manipulation and analysis, coupled with leveraging visualization tools such as Tableau, PowerBI, and Web Applications to present insights effectively. Your primary duties include: Data Analysis: Employing Python and SQL to extract, clean, and analyze data to derive actionable insights. Visualization Techniques: Using Tableau, PowerBI, and Web Applications to create intuitive and insightful visual representations of data for effective communication. Statistical Understanding: Applying statistical concepts and understanding data structures to interpret data patterns and trends accurately. 2. What we are looking for? Technical Expertise: Proficiency in Python, SQL, and data manipulation for analysis purposes. Experience in data visualization tools such as Tableau, PowerBI, and Web Applications for creating interactive and informative dashboards. Solid understanding of statistics and data structures for accurate data interpretationProven problem-solving skills and a solution-oriented mindset. Attitude & Soft Skills: Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment.

Archer is an aerospace company based in San Jose, California building an all-electric vertical takeoff and landing aircraft with a mission to advance the benefits of sustainable air mobility. We are designing, manufacturing, and operating an all-electric aircraft that can carry four passengers while producing minimal noise. Our sights are set high and our problems are hard, and we believe that diversity in the workplace is what makes us smarter, drives better insights, and will ultimately lift us all to success. We are dedicated to cultivating an equitable and inclusive environment that embraces our differences, and supports and celebrates all of our team members. What You’ll Do: As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for: Design, implement, and evaluate novel machine learning and deep learning algorithms. Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature. Conduct experiments to benchmark new techniques and evaluate model behavior. Develop tools and frameworks to support scalable and reproducible research and development. Communicate research findings to leadership in a concise, and convincing manner. Stay current with the latest developments in AI/ML and identify relevant innovations. Assist in transitioning research prototypes into production-ready systems. What You Need: M.S+ degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML. Enjoys solving less-defined and complex problems Familiarity with good SW practices and development, including code quality, version control, etc. Very strong with ML frameworks such as Pytorch, or Tensorflow Good understanding of Tran

P-150 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration. As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks’ next-generation Search product. You’ll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns. You’ll work across research, product, and infra to push the frontier of retrieval quality for enterprise AI applications — blending traditional information retrieval techniques, representation learning, and neural ranking. Beyond hands-on contributions, you will help define our long-term vision for relevance and quality, mentor senior engineers, and lead strategic efforts that raise the accuracy, reliability, and product impact of Search across Databricks. Check out our recent blog post: Reranking in Databricks AI Search for Faster, Smarter Retrieval in RAG Agents The impact you will have: Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Datab

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Scientist, Foundation Models to advance robotic embodied intelligence. In this role, you will develop algorithms that enable robots to understand their environment, interpret and execute tasks, and communicate seamlessly with humans — with a particular focus on building and training world models that allow robots to predict, plan, and generalize across complex physical tasks. Responsibilities Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies. Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution. Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations. Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions. Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication. Optimize and deploy models as production-grade solutions on RoboForce robotic platforms. Requirements PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience. Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX). Expertise in large foundation models (VLM, VLA, etc.). Strong understanding of world model architectures and action-conditioned generative modeling for robot learning. Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.). Requires 5 d

The AV Safety Software Data Engineer will play a critical role in supporting Zoox’s safety data reporting and compliance efforts. In this position, you will work with large-scale fleet data to gather, analyze, and triage events for internal safety learnings and external compliance requirements. As an AV Safety Software Data Reporting Engineer, you will operationalize defined requirements through data-driven analyses, dashboards, and workflow automations. You will implement innovative processes that are rigorous, diligent, and systematic, as well as applicable and repeatable, as Zoox continues to scale, to ensure reliable and safe operations. You will continually improve our internal data-gathering, analysis, and reporting processes and work closely with our Legal, Policy, Operations, Vehicle Engineering, Safety Design, Software, Hardware, and Communications teams to ensure a rigorous, disciplined, quantified engineering approach. A successful candidate will be able to support other Zoox safety efforts, including Operational Safety, Safety Planning, Policy, System Design, and Risk Assessment activities. In this role, you will: Create, implement, and maintain our internal and external safety data gathering, analysis, and reporting processes, and work cross-functionally with other internal organizations to ensure accurate regulatory reporting. Support the implementation of safety learnings & data programs, processes and dashboards for awareness and decision-making, including systematically ensuring representation and input from key internal stakeholders. <span style="font-size: 12pt;

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and