About the roleThis 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
ExperienceYou 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), 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.
Due to high volume, we may not actively respond to every application, but feel free to contact us at [redacted] or elsewhere if we missed your application!
