HUD

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI labs. As a Research Engineer on the Robotics team, you will develop datasets and evaluations crucial for training and assessing embodied AI systems. This role involves translating research needs into data specifications, creating methods for data validation, and conducting experiments to understand how data characteristics impact model performance. You will collaborate with internal research and engineering teams, and potentially with data vendors and buyers, to enhance robotics data offerings.

$100k - $230k

HUD is seeking a Product Engineer to transform significant product challenges into tangible user experiences across its AI data platform and marketplace. This role involves collaborating with product, design, engineering, research, and go-to-market teams to identify user pain points in AI data creation and training, define product improvements, and develop solutions. The position blends product strategy, interaction design, and full-stack development, requiring the ability to translate complex technical workflows into clear and user-friendly interfaces while retaining necessary detail.

$100k - $225k

About HUD HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs. About the role We’re looking for a Research Engineer for our Robotics team to develop the datasets and evals that make robotics data useful for training and evaluating embodied AI systems. You’ll translate open-ended research needs into data specifications, build methods to validate data, and run experiments to understand which data and structures improve model performance. Responsibilities - Research the data needs of robot learning and physical AI systems, and turn them into concrete dataset and evaluation specifications - Define data schemas, annotations, ground truth, and quality standards across robotics data types - Design collection and review protocols that external data providers can execute reliably - Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback - Run experiments and analyze model behavior to understand how data quality, coverage, and structure affect performance - Work with HUD’s research and engineering teams, and when needed with data vendors and buyers, to improve robotics data offerings Experience You may be a good fit if you have: - Experience in robotics, robot learning, embodied AI, or closely related multimodal research - Proficiency in Python and experience building data processing, analysis, or evaluation tools - Experience turning research questions into dataset specifications, experiments, and measurable quality criteria - Strong understanding of what makes robotics data useful for training or evaluation—and where it can be misleading - Attention to detail and the ability to spot subtle errors, coverage gaps, and failure modes in complex data - Experience building research tools or pipelines without a fully prescribed roadmap Strong candidates may also have: - Worked with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets - Experience with imitation learning, reinforcement learning, or vision-language-action models - Worked in unstructured problem spaces and take ownership from early research through production deployment - Early-stage startup experience and strong communication skills for collaboration across teams and time zones We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees) - Lunch and dinner for in-office employees - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. - Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place - Annual travel budget to visit either office Compensation Actual offers are adjusted for experience and location, but our base salary bands are - San Francisco (and other major US cities): $135,000 - $230,000 - Singapore: $100,000 - $175,000 - Rest of world: $100,000 - $175,000 Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!

$100k - $230k

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a growing team of researchers, engineers, and operators backed by significant VC funding. We are seeking a Research Manager to lead research focused on enhancing HUD's agent training data and evaluations for frontier models. This role involves guiding research engineers through complex projects, translating findings into scalable methods, and staying technically engaged while ensuring rigorous experimentation and impactful results. The ideal candidate will possess a deep understanding of model training dynamics, including how signals, data, and evaluation design influence outcomes.

$120k - $295k

HUD is seeking a Design Engineer to create and build user experiences across its AI data infrastructure products. This role involves making complex workflows for AI agent creation, evaluation, and training data management clear and actionable for users. You will collaborate closely with research and engineering teams, gather user feedback, and iterate on interfaces to improve usability and effectiveness. The position requires a blend of practical execution and strategic design thinking to shape how humans interact with advanced AI agents.

$100k - $225k

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI trainers. We are a rapidly growing team of researchers, engineers, and operators backed by significant VC funding. This role focuses on building the product surfaces, backend systems, and internal tools that power HUD's Reinforcement Learning (RL) data engine. You will own product surfaces end-to-end, translating ambiguous needs into polished products that enable our RL systems by working closely with research engineers and vendors.

$100k - $225k

HUD is building reliable, fair, and open infrastructure for AI data, aiming to create a valuable and trustworthy data economy for AI. We are seeking Research Engineers to develop our synthetic data pipeline. In this role, you will transform domain-specific workflows into realistic, scalable, and capability-expanding synthetic training tasks for AI agents. This involves creating tasks that are realistic enough to teach useful behavior, structured for large-scale generation, and challenging enough to push model boundaries.

$100k - $230k

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI training labs. As a growing team backed by significant VC funding, we are developing a marketplace and platform used by startups, Fortune 500 companies, and frontier labs. This role is for Research Engineers focused on building the technical foundation for training and evaluating frontier AI agents. You will be instrumental in creating new environments, enhancing data quality, and translating real-world workflows into tasks and benchmarks.

$100k - $230k