hud

Research Engineer, Benchmarks

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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”
From employer posting metadata
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
Not mentioned
Minimum experience (years)
Not specified
Work authorization
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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About HUDHUD'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 Research Engineers to build high-quality benchmarks for evaluating frontier agents on domain-specific tasks. You’ll build benchmarks that are technically rigorous, practically useful, and credible to frontier labs.
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Responsibilities Own the design, implementation, and quality of HUD’s internal agent benchmarks Work with subject-matter experts to define tasks and create domain-specific benchmarks that evaluate agents on realistic workflows Build infrastructure to reliably run models and agents against benchmark tasks Develop metrics and analyses to understand benchmark difficulty, reliability, and failure modes Validate whether benchmark performance correlates with real-world evals, customer needs, and lab expectations Write clear documentation and benchmark reports that make results legible and credible to technical audiences Experience You may be a good fit if you have: Proficiency in Python, Docker, and Linux environments Published papers or written technical blogs on relevant topics such as public benchmarks and their limitations, model failure modes, etc. - please link in your application Strong understanding of what a “good benchmark” means and what makes one realistic, reliable, and useful Experience working on environments and evals Curiosity and ability to truly understand how workflows in various domains work Strong candidates may also: Be detail-oriented and able to spot subtle inconsistencies or edge cases in tasks Be able to reason from first principles about task design, scoring, and failure modes Thrive in unstructured problem spaces Early-stage startup experience with ability to work independently in fast-paced environments 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

We’re looking for Research Engineers to build high-quality benchmarks for evaluating frontier agents on domain-specific tasks. You’ll build benchmarks that are technically rigorous, practically useful, and credible to frontier labs.

Responsibilities

  • Own the design, implementation, and quality of HUD’s internal agent benchmarks

  • Work with subject-matter experts to define tasks and create domain-specific benchmarks that evaluate agents on realistic workflows

  • Build infrastructure to reliably run models and agents against benchmark tasks

  • Develop metrics and analyses to understand benchmark difficulty, reliability, and failure modes

  • Validate whether benchmark performance correlates with real-world evals, customer needs, and lab expectations

  • Write clear documentation and benchmark reports that make results legible and credible to technical audiences

Experience

You may be a good fit if you have:

  • Proficiency in Python, Docker, and Linux environments

  • Published papers or written technical blogs on relevant topics such as public benchmarks and their limitations, model failure modes, etc. - please link in your application

  • Strong understanding of what a “good benchmark” means and what makes one realistic, reliable, and useful

  • Experience working on environments and evals

  • Curiosity and ability to truly understand how workflows in various domains work

Strong candidates may also:

  • Be detail-oriented and able to spot subtle inconsistencies or edge cases in tasks

  • Be able to reason from first principles about task design, scoring, and failure modes

  • Thrive in unstructured problem spaces

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

  • 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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