Job Description
Experience: Technical aptitude and learning potential matter more than years Pay: $100k-$200k, full time Location: San Francisco, CA, US or Singapore (on-site) Visa: Relocation and visa support available for strong candidates The role Build high-quality benchmarks for evaluating frontier agents on domain-specific tasks.
You will create benchmarks that are technically rigorous, practically useful, and credible to frontier labs. What you'll do
- Own the design, implementation, and quality of HUD's internal agent benchmarks
- Work with subject-matter experts to define realistic domain-specific tasks
- Build infrastructure to run models and agents reliably against benchmark tasks
- Develop metrics and analyses for benchmark difficulty, reliability, and failure modes
- Validate whether benchmark performance correlates with real-world evaluations, customer needs, and lab expectations
- Write clear documentation and benchmark reports for technical audiences
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What we're looking for
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- Proficiency in Python, Docker, and Linux environments
- Published papers or technical blogs about benchmarks, model failure modes, or related topics
- A strong understanding of what makes a benchmark realistic, reliable, and useful
- Experience with environments and evaluations
- Curiosity and the ability to understand how workflows in unfamiliar domains actually work
- First-principles reasoning about task design, scoring, and failure modes
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Strong signals
- Detail orientation and an eye for subtle inconsistencies and edge cases
- Independent work in unstructured problem spaces
- Early-stage startup experience
- Strong communication across time zones
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