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Senior/Staff Deep Reinforcement Learning Engineer

San Francisco, CA💼 Full-time💰 $168,000–$168,000🗓 2026-03-27 → 2026-07-31

Core

Design, train, and deploy deep reinforcement learning policies for real-time autonomous vehicle driving decisions.

Role type

Senior/Staff Deep Reinforcement Learning Engineer

Builds

Real-time autonomous delivery systems using learned planning and prediction models

Domain

Autonomous driving / Robotics

Deliverable

production ML models

Required skills

Deep reinforcement learning, JAX, GPU-accelerated simulation, distributed training infrastructure, policy gradients, value functions, model-based RL, sim-to-real transfer, AI coding tools

Preferred skills

Publications at top ML/robotics venues, building GPU-accelerated simulators, shipping learned components in production robotics stacks

Technologies

JAX, GPU clusters, AI coding tools (Claude Code, Codex, Cursor)

Responsibilities

Formulate complex driving tasks as RL problems with well-shaped reward functions; Design and train model-based deep RL agents at massive scale; Build and maintain distributed training infrastructure; Build agentic optimization systems for automated experimentation and policy iteration

Seniority

Senior/Staff, hands-on IC

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