Research Engineer, Infrastructure

Highlights

• Build infra powering post-training of open-weight models for legal work.
• Own distributed rollout systems for long-horizon agentic legal workflows.
• Ship research to production with serving, evals, and internal tooling.

What they offer

• Offers Equity
• Offers Bonus

Ideal candidate

Hands-on infrastructure engineer who owns demanding ML systems end-to-end and thrives debugging across the stack. You love partnering with researchers to make training fast, reliable, and easy to iterate.

Requirements

• Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
• Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
• Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
• Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
• Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.