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About the Role

HUD is seeking a Research Engineer for its Robotics team to develop datasets and evaluations for training and evaluating embodied AI systems. This role involves translating research needs into data specifications, building validation methods, and running experiments to optimize model performance.

Responsibilities

Research data needs for robot learning and physical AI systems, translating them into dataset and evaluation specifications.
Define data schemas, annotations, ground truth, and quality standards for various robotics data types.
Design collection and review protocols for external data providers.
Build tools and validation workflows to audit datasets, identify quality issues, and provide feedback.
Run experiments and analyze model behavior to understand the impact of data quality, coverage, and structure on performance.
Collaborate with HUD's research and engineering teams, and external data vendors and buyers, to enhance robotics data offerings.

Requirements

Experience in robotics, robot learning, embodied AI, or related multimodal research.
Proficiency in Python and experience building data processing, analysis, or evaluation tools.
Experience translating research questions into dataset specifications, experiments, and measurable quality criteria.
Strong understanding of the utility and potential pitfalls of robotics data for training and evaluation.
Attention to detail for identifying subtle errors, coverage gaps, and failure modes in complex data.
Experience building research tools or pipelines without a fully prescribed roadmap.
Experience with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets.
Experience with imitation learning, reinforcement learning, or vision-language-action models.
Experience working in unstructured problem spaces and taking ownership from research to deployment.
Early-stage startup experience.
Strong communication skills for cross-team and cross-time zone collaboration.

Skills

Python
Data processing
Data analysis
Data evaluation
Dataset specification
Experimentation
Quality criteria
Robotics data analysis
Imitation learning
Reinforcement learning
Vision-language-action models

Location

San Francisco
Singapore
Remote (with 70-80% overlap with SF or SG time zones)

Work Type

Full-time
Remote

Experience Level

Technical aptitude and learning potential prioritized over years of experience.

Salary/Compensations

Competitive compensation

Benefits

100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US employees)
Lunch and dinner when in the office (in-office employees)
Company-wide holiday break (Christmas Eve to New Year’s Day) in addition to PTO and paid holidays
Equinox membership
401k
Commuter benefits (US employees)
Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
Support for relocation and visas for strong full-time candidates to the US or Singapore.

About the Company

HUD is building infrastructure for RL training data and evals for frontier AI agents, and a marketplace to sell these to frontier labs.
The platform is used by frontier labs, Fortune 500 companies, and startups.
HUD has raised $16M from top VCs and was part of YC W25.
The team consists of approximately 25 people, including International Olympiad medalists, serial AI startup founders, and researchers with publications at top AI conferences.
The company is in a growth phase with 8 figures in funding and strong demand.