Lead Engineer, Reinforcement Learning & Scenario Generation

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Requirements

• Develop RL algorithms that can help with terrain intelligence and social navigation behaviors.
• Design, build, and optimize large-scale RL training pipelines (distributed compute, GPU clusters, containerized workflows).
• Implement curriculum learning, domain randomization, and multi-agent RL strategies.
• Optimize RL model performance, sample efficiency, and stability across thousands to millions of simulation steps.
• Build automated tools for experiment orchestration, rollout collection, and metrics visualization.
• Develop procedural generation pipelines for synthetic environments, agents, and dynamic behaviors.
• Build tools to generate long-tail scenarios, sudden appearance of objects, traffic behaviors, rare events, and environmental variations.
• Create systems for configuration, validation, and scoring of generated scenarios.
• Collaborate with autonomy, ML, and safety teams to map real-world failures into repeatable synthetic simulation cases.
• Design APIs to connect RL agents, scenario generators, planners, and environment simulators.
• Debug and optimize simulation performance (real-time speed, determinism, reproducibility).
• Work with 3D assets, traffic models, mapping systems (e.g., Isaac Sim, CARLA, Unity, Gazebo).
• Partner with autonomy, data, and modeling teams to define training objectives and scenario requirements.
• Translate real-world logs and edge cases into parameterized procedural content.
• Document tools, frameworks, and workflows for internal users.

Benefits

• Generous Paid Time Off
• 401k Matching
• Retirement Plan
• Visa Sponsorship
• Four Day Work Week
• Generous Parental Leave
• Tuition Reimbursement
• Relocation Assistance