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 brings together five International Olympiad medalists across IOI, ILO and IPhO, researchers published at NeurIPS and ICLR, and engineers and researchers from Google DeepMind, Amazon, AWS, Meta, Qwen, GLM, and Mercor. It also includes operators from BCG and Uber, the first security hire at one of the largest crypto exchanges, serial AI startup founders, former quant researchers, artists and the former #1 ranked Catan player in the world.

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