AIML - Machine Learning Research Lead, RL Agents, MLR

What you'll do

• Lead research on RL and post-training for agentic capabilities, including reward design, training, and evaluation.
• Build synthetic task and environment-generation pipelines and own core RL research codebases and infrastructure.
• Manage and mentor a small team while remaining hands-on with experiments, code, and cross-organization research.

What they ask for

• PhD in machine learning or a related field, or equivalent research experience.
• 7–10+ years of research experience beyond PhD in industry or as an academic research lead.
• Strong RL and/or large-model post-training track record, demonstrated through publications, open-source contributions, or shipped systems.
• Leadership experience setting research direction and directing others’ work; experience owning ML infrastructure, frameworks, and codebases; strong hands-on engineering skills.

Nice to have

• Experience taking research to product or production impact.
• Familiarity with efficiency-aware modeling, hardware-aware methods, open-endedness, evolutionary computation, environment design, multi-agent systems, or self-improving systems.

Pay

$216,200 and $394,000 (base pay range; USD)

Tools

RL, post-training, tool calling, synthetic data, large training codebases, mixture-of-experts, quantization, distillation

AI focus

Develops reinforcement learning and post-training for agentic AI, including tool use, coding, interactive tasks, synthetic environments, and deployment-aware methods.