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Research Engineer, Machine Learning (RL Velocity)

AI Engineer Remote-friendly within a US-based role with required travel and possible 25% office attendance

Job details

Not specified Salary
Remote-friendly within a US-based role with required travel and possible 25% office attendance Eligibility
Staff Experience
Not specified Employment

About this role

Role overview

This role owns the efficiency and reliability of the reinforcement-learning research stack: the infrastructure, tooling, and services that allow researchers to iterate rapidly on training runs. You will remove bottlenecks across debugging, performance, reliability, and system design, creating leverage for many research teams and helping improve the speed at which new model capabilities can be developed.

Responsibilities

- Build and improve the training infrastructure used by reinforcement-learning researchers day to day. - Diagnose, profile, and eliminate bottlenecks across the research stack, including through architectural changes. - Partner with researchers and adjacent engineering teams to understand workflow problems and ship effective tools. - Own the reliability and performance of research runs from start to finish. - Contribute to technical decisions that shape reinforcement learning at large scale. - Work across layers ranging from low-level performance engineering to reinforcement-learning algorithms.

Requirements

- Strong software-engineering fundamentals and a record of building performant, dependable systems. - Experience with machine-learning infrastructure, distributed systems, or research tooling. - An interest in enabling other people’s work through high-leverage platforms rather than only individual experiments. - Comfort moving between systems engineering and machine-learning concepts. - A practical, delivery-focused approach with strong ownership and low ego.

Nice to have

Experience with large-scale distributed training for reinforcement learning, pre-training, or post-training; familiarity with JAX, PyTorch, or comparable frameworks; and experience operating at the boundary between research and infrastructure are valuable.

Benefits and work setup

The role is remote-friendly but requires travel and may be based from offices in San Francisco or New York City. The general expectation is that staff spend at least 25% of their time in an office, with some roles requiring more. Visa sponsorship may be available depending on the role and candidate. The listed annual salary range is $500,000–$850,000 USD.

Skills detected in the listing

Machine Learning
Detected Sep 19, 2026
Last verified Sep 19, 2026

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