Research Engineer, Infrastructure

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Research Engineer, Infrastructure in USA new

Harvey
Full time
Email

USA
10/31/2026
Report

Remote

Responsibilities

Scale the post-training stack for supervised fine-tuning and reinforcement learning on open-weight models.
Build distributed rollout infrastructure coordinating model inference, tool execution, and training-experience collection.
Create reproducible agent environments for model interaction with documents, tools, and external systems.
Own training-run performance and reliability, including GPU utilization, checkpointing, failure recovery, and observability.
Identify and remove training and inference bottlenecks.
Build internal systems for training-data management, evaluation, experiment tracking, and job launching.
Integrate models into production, including serving, latency, cost, and online evaluation.
Partner with researchers to turn experimental workflows into dependable systems.

Requirements

Experience building ML infrastructure, distributed systems, or research tooling with ownership of performance, reliability, and operations.
Strong Python and generalist software engineering skills across backend services, data systems, and internal tools.
Familiarity with PyTorch, JAX, or similar ML frameworks.
Experience with distributed training or inference and 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.
Ability to make practical build-versus-buy decisions, partner with researchers, and ship quickly as needs evolve.

Salary: $230k - $340k/yr

Harvey

Harvey is domain-specific AI for legal and professional services. Adopted by Fortune 500 companies like AT&T, Verizon, Cox, Koch, KKR, Bridgewater, more than 100,000 lawyers across 2,400+ customers in 70 countries and over 75% of AmLaw 100 law firms rely on Harvey to advance legal expertise faste...

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