Machine Learning Research Lead, RL Agents

What you'll do

• Lead research on RL and post-training for agentic capabilities including reward optimization and verifier design.
• Build and own pipelines for synthetic data, task generation, and interactive training environments.
• Drive the development of codebases and infrastructure for core RL research efforts.
• Manage and mentor a small team of senior researchers and research engineers.
• Execute experiments and write code to solve the team's most important technical problems.
• Optimize post-training research for on-device and hybrid compute constraints.
• Publish research in top venues and engage with the broader academic community.

What we're looking for

• PhD in machine learning or a related field, or equivalent research experience.
• 7-10+ years of research experience beyond a PhD in industry or as an academic research lead.
• Strong track record in RL and/or post-training of large models demonstrated through publications, open-source contributions, or shipped systems.
• Leadership experience setting and defending research directions and directing the work of others over multiple years.
• Experience owning ML infrastructure, frameworks, and codebases, including open-source research frameworks or environment suites.
• Strong engineering skills with the ability to work hands-on in large training codebases.
• Experience taking research from idea to product or production impact (preferred).
• Familiarity with efficiency-aware modeling, including small models, quantization, distillation, or hardware-aware method design (preferred).