Research Engineer, Benchmarks

HUD; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Top-tier medical, dental, and vision (

Lunch and dinner in office

Holiday break & PTO

Equinox membership

401k

Commuter benefits

Unlimited tokens for AI tools

Job summary

HUD is seeking Research Engineers to build high-quality benchmarks for evaluating frontier agents on domain-specific tasks. You will own the design of HUD's internal agent benchmarks and work with experts to define tasks that mirror realistic workflows.

You will develop infrastructure to run models and agents against benchmarks, create metrics to assess difficulty and failure modes, and ensure results align with real-world needs and lab expectations, with clear documentation and reports.

Qualifications

• Proficiency in Python, Docker, and Linux environments.
• Published papers or technical blogs on benchmarks and their limitations, model failure modes, etc.
• 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 understand workflows across domains.

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.

Skills

Python

Research

Benchmark design

Eval frameworks

Cross-domain workflows

Education

Bachelor's degree in a relevant field

Tools

Docker

Linux

Job description

About HUD

HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.

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: ~15 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 high revenue growth. We’re scaling profitably and quickly to meet very strong demand.

Logistics

• Employment: Full‑time.

• Location: On‑site only, for now. You can join the team in the San Francisco Bay Area or Singapore offices.

• 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

• 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.

Due to high volume, we may not actively respond to every application, but feel free to contact us at [e-mail] or elsewhere if we missed your application!