Senior Research Infrastructure Engineer

Description

The company builds reliable, fair, and open infrastructure for AI data. Data should be valuable to the people who create it and trustworthy for the labs that train on it.

The team has grown quickly to about 25 people, mostly full-time in-person with some remote members.

Funding totals $16M from top VCs and YC (W25).

The marketplace and platform are used by startups, Fortune 500 companies, and frontier labs.

The role speeds up research on training and evaluating frontier AI agents by building the software researchers use to iterate on environments, collect trajectories, and assess model behavior.

You will work with research engineers to learn what they are investigating, find where experiments slow down, and turn research code into dependable, reusable systems.

The team includes 4 International Olympiad medalists (IOI, ILO, IPhO), a former 1 ranked Catan player in the world, serial AI startup founders, and researchers with publications at ICLR, NeurIPS, and other venues.

The company has 8 figures in funding and is growing quickly and profitably to meet strong demand.

Responsibilities

• Own the tools, pipelines, and execution infrastructure that help researchers explore ideas, reproduce results, and scale promising approaches.
• Build reliable environment execution, trajectory collection, and evaluation at scale to support research on agent behavior.
• Create reusable tools, APIs, and pipelines so researchers can launch experiments, manage datasets and configurations, and inspect trajectories and evaluation results.
• Turn research prototypes and experimental workflows into tested, documented software others can reuse and extend.
• Design experiments that reveal model behavior, agent failure modes, and data quality issues.
• Speed up experiments, make them reproducible, and lower their cost by improving orchestration, observability, and recovery from failed runs.
• Work with research and engineering to turn changing research needs into infrastructure priorities and architecture decisions, and own systems from build through ongoing operation.

Requirements

• Solid software engineering basics and strong Python, with a history of maintainable systems that others use.
• Experience owning backend services, data pipelines, developer tools, or infrastructure from design through deployment and operation.
• Good judgment on APIs, data models, asynchronous workloads, and the trade-offs in building reliable systems.
• Comfortable with Docker, Linux, and cloud infrastructure, and able to debug failures in application code and the systems it runs on.
• Able to work closely with researchers, understand experimental workflows, and turn open-ended research needs into useful software.
• Sound independent judgment: set priorities, make practical architecture calls, and improve systems as users and workloads grow.
• Strong candidates may also have: working knowledge of reinforcement learning, including environments, rollouts, reward signals, and evaluation workflows.
• Strong candidates may also have: experience building research infrastructure, ML pipelines, or tools that made a research team faster.
• Strong candidates may also have: familiarity with distributed job execution, containerized environments, or high-concurrency workloads.
• Strong candidates may also have: a track record of improving experiment reproducibility, data lineage, or visibility into complex pipeline failures.
• Technical aptitude and learning potential are valued over years of experience, so motivated candidates are encouraged to apply even if they do not meet every criterion.

Conditions

Full-time employment.

Offers are adjusted for experience and location. Base salary bands: San Francisco and other major US cities $175,000 - $260,000; Singapore $130,000 - $195,000; rest of world $105,000 - $195,000.

Experience listed: 5+ years.

Visa: US citizen or visa holders only.

Offices in San Francisco and Singapore. Remote candidates are considered if their working hours overlap 70-80% with San Francisco or Singapore time.

Relocation and visa support is offered to strong full-time candidates moving to the US or Singapore.

Applications are reviewed on a rolling basis. The process includes 2 technical interviews and a 2-3 day work trial.

Benefits

• Competitive compensation.
• Top-of-the-line medical, dental, and vision coverage, 100% covered for US and Singapore employees.
• Lunch and dinner for in-office employees.
• The company closes from Christmas Eve to New Year's Day, in addition to PTO and paid holidays.
• 401k with a 4% match.
• Equinox membership and commuter benefits for US employees, and a health and wellness stipend for Singapore employees.
• Unlimited access to tokens for ChatGPT, Claude Code, Cursor, and similar tools. No one on the token usage leaderboard has ever hit a limit, so the actual cap is unknown.
• Offices on the top floor in San Francisco's Union Square and Singapore's Raffles Place.
• Annual travel budget to visit either office.