Staff Applied Research Engineer

CoreWeave•Sunnyvale, CA

1d•$207,000 - $275,000•Onsite

About The Position

The OpenPipe team at CoreWeave is building tools to help agents learn from experience, a critical step towards making agents reliable for long, autonomous tasks. They are systematically identifying and solving major bottlenecks in AI agent development. Recent releases include ART (a library for RL), RULER (a general-purpose reward function), and Serverless RL (an API for RL practitioners). The team is focused on solving challenges like building simulated environments and improving data efficiency in training methods. This is a hard-tech bet with significant technical risk but low market risk, as a self-improving agent could capture a large portion of the inference market.

Requirements

8+ years of experience in machine learning or applied research, or a PhD with 4+ years of relevant industry experience.
Demonstrated success developing LLM training methods or systems that produce meaningful improvements on real-world tasks.
Deep expertise in LLM post-training, including supervised fine-tuning, reinforcement learning, on-policy distillation, reward modeling, and policy optimization.
Strong research judgment, including the ability to identify high-impact problems, design rigorous experiments, and make decisions from ambiguous results.
Experience taking research ideas from initial hypothesis through implementation, evaluation, and production deployment.
Proven ability to set technical direction, lead complex cross functional initiatives, and mentor other engineers.
Ability to learn fast and ship.
Must be a U.S. person (U.S. citizen or national, U.S. lawful permanent resident, refugee, or asylee) or eligible to access export controlled information without required authorization, or eligible and likely to obtain required export authorization.

Nice To Haves

Publications, open source contributions, or other demonstrated research impact in reinforcement learning, LLM post-training, or agent learning.
Deep experience with distributed training, GPU optimization, and large-scale model training systems.

Responsibilities

Generate and investigate research ideas towards solving the remaining obstacles to continuous learning in production.
Work with the broader OpenPipe team to validate research directions across real customer tasks.
Touch everything from CUDA kernels to high-performance LLM tracing dashboards.
Drive the team's own roadmap and priorities.