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Salary: USD 175,000 - 260,000 / annual
HUD is building infrastructure for AI data, enabling researchers and labs to train frontier AI models on trustworthy, valuable datasets. The company is backed by $16M in funding from top VCs and Y Combinator (W25) and operates a marketplace and platform used by startups, Fortune 500 companies, and frontier AI labs.
As a Senior Research Infrastructure Engineer, you will accelerate research on training and evaluating frontier AI agents by building the software and infrastructure that enable HUD's research team to iterate on environments, collect trajectories, and evaluate model behavior at scale.
You will work closely with research engineers to understand their experimental questions, identify bottlenecks in their workflows, and transform research prototypes into reliable, reusable systems. Your core responsibilities include:
- Building infrastructure for reliable environment execution, trajectory collection, and evaluation at scale
- Developing reusable tools, APIs, and pipelines that let researchers launch experiments, manage datasets and configurations, and inspect results
- Converting research prototypes and experimental workflows into tested, documented software
- Designing experiments to understand model behavior, agent failure modes, and data quality issues
- Improving experimentation speed, reproducibility, and cost-efficiency through better orchestration, observability, and failure recovery
- Partnering with research and engineering teams to translate research needs into infrastructure priorities and architecture decisions, owning systems from implementation through ongoing operation
The team is ~25 people, mostly full-time in-person but with some remote flexibility. The company includes 4 International Olympiad medalists, serial AI startup founders, and researchers with publications at top venues like ICLR and NeurIPS. HUD has 8 figures in funding and is scaling profitably to meet strong demand.
The role offers competitive compensation, comprehensive medical/dental/vision coverage, lunch and dinner for in-office employees, company-wide holiday break, 401k with 4% match, Equinox membership, commuter benefits, unlimited access to AI tokens (ChatGPT, Claude, Cursor), and an annual travel budget to visit either office.
REQUIREMENTS:
Core requirements:
- Strong software engineering fundamentals and proficiency in Python, with a track record of building maintainable systems used by others
- Ownership experience with backend services, data pipelines, developer tools, or infrastructure from design through deployment and operation
- Sound judgment about APIs, data models, asynchronous workloads, and tradeoffs in building reliable systems
- Comfort with Docker, Linux, cloud infrastructure, and debugging failures across application and system layers
- Ability to work closely with researchers, understand experimental workflows, and translate open-ended research needs into useful software
- Independent technical judgment to set priorities, make pragmatic architecture decisions, and improve systems as users and workloads grow
Strong candidates may also have:
- Working knowledge of reinforcement learning (environments, rollouts, reward signals, evaluation workflows)
- Experience building research infrastructure, ML pipelines, or tools that accelerated research teams
- Familiarity with distributed job execution, containerized environments, or high-concurrency workloads
- Track record improving experiment reproducibility, data lineage, or visibility into complex pipeline failures
The company prioritizes technical aptitude and learning potential over years of experience and encourages motivated candidates to apply even if they don't meet all criteria.
