About HUD

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.

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 from Blue Shield of CA (US employees)

• Lunch and dinner when you’re in the office (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)

• 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.

Due to high volume, we may not actively respond to every application, but feel free to contact us at recruiting@hud.so or elsewhere if we missed your application!