hud

Research Engineer (General)

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Older posting · still listed ·

  • onsite
  • FullTime
  • Engineering & Research
  • San Francisco
  • Singapore
  • Remote (Asia)
  • Remote (North America)
Work arrangement
onsite
Employment
FullTime
Stated compensation
USD 100,000–230,000 1 YEAR
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Requirements

3 with evidence6 unclear or unstated
Remote policy
onsite
“Provider workplace type: onsite”
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Geographic scope
SG
“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.”
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Timezone / hours
Strong communication skills for remote collaboration across time zones; 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.
“Strong communication skills for remote collaboration across time zones”
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Employment type
FullTime
Compensation
USD 100,000–230,000 1 YEAR
6 fields not stated in this posting
Employer sponsorship
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Citizenship requirement
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Minimum experience (years)
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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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
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This is a general application for candidates who are unsure which research focus - QC Automation, Benchmarks, or Synthetic Data - they would be a fit for. We would love to meet you and figure it out together. However, if you already have a focus in mind, please apply to only that application. We're looking for Research Engineers to build the technical foundation for training and evaluating frontier AI agents. You’ll build the systems for creating new environments, improve data quality, and translate real-world workflows into tasks and benchmarks. Responsibilities Build systems for creating, running, evaluating, and improving agent training environments Design experiments to understand model behavior, agent failure modes, and data quality issues Develop tools that help researchers, engineers, and data vendors create higher-quality tasks, trajectories, and feedback loops Work across the full lifecycle of agent training data - task design, environment setup, trajectory collection, evaluation, and validation Partner with external vendors to identify bottlenecks and improve the quality and throughput of HUD’s data engine Build metrics and analyses that help us understand whether our tasks, environments, and evals are actually useful for training frontier agents Experience You may be a good fit if you have: Proficiency in Python, Docker, and Linux environments Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training Strong attention to detail and the ability to spot subtle inconsistencies in data, model behavior, or task design Experience building tools, pipelines, experiments, or infrastructure without a fully prescribed roadmap Early-stage startup experience with ability to work independently in fast-paced environments Strong candidates may also have: Experience building internal tools, research infrastructure, or data pipelines Experience designing metrics and validation workflows A background in competitive programming, Olympiad medaling, research, or unusually strong independent project experience Thrive in unstructured problem spaces Strong communication skills for remote collaboration across 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), the former #1 ranked Catan player in the world, 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 401k with a 4% match Other perks including an Equinox membership 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 recruiting@hud.so or elsewhere if we missed your application!
Original formatting and links

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

This is a general application for candidates who are unsure which research focus - QC Automation, Benchmarks, or Synthetic Data - they would be a fit for. We would love to meet you and figure it out together. However, if you already have a focus in mind, please apply to only that application.

We're looking for Research Engineers to build the technical foundation for training and evaluating frontier AI agents. You’ll build the systems for creating new environments, improve data quality, and translate real-world workflows into tasks and benchmarks.

Responsibilities

  • Build systems for creating, running, evaluating, and improving agent training environments

  • Design experiments to understand model behavior, agent failure modes, and data quality issues

  • Develop tools that help researchers, engineers, and data vendors create higher-quality tasks, trajectories, and feedback loops

  • Work across the full lifecycle of agent training data - task design, environment setup, trajectory collection, evaluation, and validation

  • Partner with external vendors to identify bottlenecks and improve the quality and throughput of HUD’s data engine

  • Build metrics and analyses that help us understand whether our tasks, environments, and evals are actually useful for training frontier agents

Experience

You may be a good fit if you have:

  • Proficiency in Python, Docker, and Linux environments

  • Experience working on benchmarks and evals - you can reason about what makes a task realistic, a rubric reliable, an environment usable, and a trajectory useful for RL training

  • Strong attention to detail and the ability to spot subtle inconsistencies in data, model behavior, or task design

  • Experience building tools, pipelines, experiments, or infrastructure without a fully prescribed roadmap

  • Early-stage startup experience with ability to work independently in fast-paced environments

Strong candidates may also have:

  • Experience building internal tools, research infrastructure, or data pipelines

  • Experience designing metrics and validation workflows

  • A background in competitive programming, Olympiad medaling, research, or unusually strong independent project experience

  • Thrive in unstructured problem spaces

  • Strong communication skills for remote collaboration across 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), the former #1 ranked Catan player in the world, 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

  • 401k with a 4% match

  • Other perks including an Equinox membership 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 recruiting@hud.so or elsewhere if we missed your application!

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