Member of Technical Staff, Infrastructure

Job summary

Responsibilities

As a Member of Technical Staff, Infrastructure in Harvey Research, you’ll build the systems that power how we adapt and improve leading open-weight models for legal work.

• Scale our post-training stack, supporting SFT and RL on leading open-weight models.
• Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
• Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
• Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
• Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.

What they're looking for

• 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.

Tech stack

• Python
• PyTorch
• JAX