Applied Research Forward-Deployed Reinforcement Learning

Skills

About the Role

You will lead applied reinforcement-learning programs from ambiguous customer problems through deployed improvement loops. You will turn workflows into environments, evaluations, baselines, and reward signals; run post-training experiments; deploy successful results; and create reusable research and platform artifacts.

Requirements

• Customer-embedded technical work, research engineering, technical founding, applied ML consulting, or end-to-end post-training experience
• Experience building and debugging model-training, post-training, agent, or evaluation loops
• Experimental judgment, including baselines, trace inspection, and failure attribution
• Python
• Ability to build reproducible artifacts for researchers and engineers
• Ability to own ambiguous problems and communicate with partners

Responsibilities

• Lead technical and business discovery to define research plans, success measures, environments, and baselines
• Run reinforcement learning, distillation, and post-training experiments tied to deployment outcomes
• Build agent systems with tool use, memory, recovery, long-horizon capabilities, and human oversight
• Make deployment and adoption decisions and create reusable artifacts

Benefits

• Flexible work
• Visa sponsorship and relocation support
• Team off-sites and conference attendance