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Research Engineer, Robotics Data

San Francisco, California, United States

Pay
Multiple pay statements — pay source
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
San Francisco (and other major US cities): $135,000 - $230,000 Singapore: $100,000 - $175,000 Rest of world: $80,000 - $175,000
Singapore: $100,000 - $175,000 Rest of world: $80,000 - $175,000 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!
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Work setup
Remote stated — work setup source
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.
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Employment
Unconfirmed

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore.
Read the full posting
Apply at hud

What you’ll work on

Full posting

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.

  • 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

From the employer’s posting
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
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
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

What you’ll bring

All qualifications

Core experience

  • Experience in robotics, robot learning, embodied AI, or closely related multimodal research
  • Experience with imitation learning, reinforcement learning, or vision-language-action models
  • 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
  • Experience building research tools or pipelines without a fully prescribed roadmap
Qualification wording
Experience in robotics, robot learning, embodied AI, or closely related multimodal research
Experience with imitation learning, reinforcement learning, or vision-language-action models
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
Experience building research tools or pipelines without a fully prescribed roadmap

Tools in this posting

  • Python
Source — Tool mentions in context
- 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

Benefits in the posting

Full benefits wording
  • Competitive compensation
  • 100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US 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)

From the employer’s posting.

About hud

HUD's mission is to build reliable, fair and open infrastructure for AI data.

In the employer’s words · Read in context

Job description

View original posting ↗

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 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.

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: $80,000 - $175,000

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!

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
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
More source context
San Francisco (and other major US cities): $135,000 - $230,000 Singapore: $100,000 - $175,000 Rest of world: $80,000 - $175,000

More relevant text appears in the full description.

Location & working pattern

San Francisco, California, United States

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.
More source context
- 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.
Work authorization
- 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.
Status in our records
Active
First seen by us
Oct 1, 2026
Recorded sightings
3
Last seen by us
Oct 7, 2026
Employer says posted
Sep 28, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

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