Staff Applied Research Engineer

Join the OpenPipe team at CoreWeave as a Staff Applied Research Engineer. In this role, you will work on building tools to help agents learn from experience, making them reliable enough to perform long tasks autonomously. You will tackle major bottlenecks in the development of self-improving agents and have the opportunity to touch many parts of the technology stack. This is an excellent opportunity for someone looking to make a significant impact in the field of AI and machine learning.

• Generar e investigar ideas de investigación para resolver los obstáculos restantes en el aprendizaje continuo en producción.
• Trabajar con el equipo de OpenPipe para validar estas direcciones de investigación en tareas reales de clientes.
• Desarrollar métodos o sistemas de entrenamiento de LLM que produzcan mejoras significativas en tareas del mundo real.
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency