Senior Applied Research Engineer

Join the OpenPipe team at CoreWeave, where you'll work on groundbreaking tools to help agents learn from experience. As a Senior Applied Research Engineer, you'll tackle major bottlenecks in training self-improving agents and contribute to the future of autonomous task performance. This role offers a unique opportunity to work on cutting-edge technology with a focus on continuous learning in production.

• Identifying and solving major bottlenecks in the development of self-improving agents.
• Generating and investigating research ideas to overcome obstacles to continuous learning in production.
• Collaborating with the OpenPipe team to validate research directions across real customer tasks.
• You have trained LLMs to be SOTA on specific tasks. You have opinions on whether sequence-level or token-level importance ratios are more effective. You probably shared the ScaleRL paper in your group chats, and kicked off a few ablations after you read it
• Beyond your role's specific qualifications, we're looking for strong engineers with great taste. The most important qualification by far is that you learn fast and can ship
• This is an excellent role for someone looking to found their own company in the future
• Experience developing, evaluating, and deploying machine learning models in production environments
• Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Robotics, or a related technical field
• Strong understanding of LLM post-training techniques, including supervised fine-tuning, reinforcement learning, and on-policy distillation
• Strong programming skills in Python and hands on experience with modern ML frameworks such as PyTorch or JAX
• 4+ years of experience in machine learning, or a PhD with 2+ years of relevant industry experience, with a strong focus on model training
• Strong research and problem solving skills, with the ability to work effectively in ambiguous, fast moving environments
• Experience with distributed training, GPU acceleration, and large scale model training systems
• Publications, open source contributions, or demonstrated research impact in LLM post-training or agent learning
• Experience leading technically complex projects or mentoring other engineers
• We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match