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Senior Research Infrastructure Engineer

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Senior Research Infrastructure Engineer in Remote new

  • Americas

Responsibilities

  • Build infrastructure for reliable environment execution, trajectory collection, and evaluation of agent behavior at scale.
  • Develop reusable tools, APIs, and pipelines for launching experiments, managing datasets and configurations, and inspecting trajectories and evaluation results.
  • Turn research prototypes and experimental workflows into tested, documented software that researchers can reuse and extend.
  • Design experiments to understand model behavior, agent failure modes, and data quality issues.
  • Improve orchestration, observability, failure recovery, reproducibility, experimentation speed, and cost efficiency.
  • Partner with research and engineering teams to translate evolving needs into infrastructure priorities and architecture decisions, owning systems through operation.

Requirements

  • Strong software engineering fundamentals and proficiency in Python, with experience building maintainable systems used by others.
  • Experience owning backend services, data pipelines, developer tools, or infrastructure from design through deployment and operation.
  • Sound judgment regarding APIs, data models, asynchronous workloads, and reliable-system tradeoffs.
  • Comfort with Docker, Linux, cloud infrastructure, and debugging failures across application code and its underlying systems.
  • Ability to work with researchers and translate open-ended experimental needs into useful software.
  • Independent technical judgment for prioritization, pragmatic architecture decisions, and scaling systems with their users and workloads.
  • Preferred: working knowledge of reinforcement learning, including environments, rollouts, reward signals, and evaluation workflows.
  • Preferred: experience with research infrastructure, ML pipelines, distributed job execution, containerized environments, high-concurrency workloads, experiment reproducibility, data lineage, or complex pipeline failure visibility.
  • Technical aptitude and learning potential are prioritized over a specific number of years of experience.

Benefits

  • Competitive compensation with base salary bands of $175,000-$260,000 in San Francisco and other major US cities, $130,000-$195,000 in Singapore, and $105,000-$195,000 elsewhere.
  • 100% covered medical, dental, and vision insurance for US and Singapore employees.
  • Lunch and dinner for in-office employees.
  • Company-wide holiday break from Christmas Eve through New Year's Day, in addition to PTO and paid holidays.
  • 401(k) with a 4% match.
  • Equinox membership and commuter benefits for US employees, plus a health and wellness stipend for Singapore employees.
  • Access to tokens for ChatGPT, Claude Code, Cursor, and similar tools.
  • Full-time work in San Francisco or Singapore, or remote work with 70-80% overlap with either time zone.
  • Relocation and visa support for strong full-time candidates to the US or Singapore.
  • Annual travel budget to visit either office; applications are rolling and the process includes two technical interviews and a 2-3 day work trial.

Salary: $105k - $260k/yr

HUD

The platform to build RL environments. We help improve frontier models across diverse capabilities and help build post-training datasets for doing RFT.

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