Senior Reinforcement Learning Engineer for Autonomous Driving Core

Wayve; Sunnyvale (CA); Hybrid; USD 312,000 - 389,000; Full time

Job summary

Wayve is seeking a Senior/Staff Machine Learning Engineer in Sunnyvale to advance reinforcement learning for end-to-end driving models. You will iterate from design through large-scale experiments and integrate successful methods into driving systems.

You will lead RL work within AV Core and Core Model Safety, collaborating with researchers and engineers to push the boundaries of safe, data-driven driving policies with robust evaluation and deployment readiness.

Qualifications

• Strong track record developing and validating reinforcement learning methods on complex problems.
• Deep understanding of modern RL fundamentals, including policy/value learning and off-policy methods.
• Hands-on experience with behaviour cloning and RL-related techniques.
• Proficiency in Python and PyTorch with solid ML engineering practices.
• Excellent experimental judgement and ability to drive clear technical decisions.
• Senior-level ownership and collaboration across research and engineering.

Responsibilities

• Shape and execute the RL roadmap for Driving Core / Core Model Safety with measurable goals.
• Develop and evaluate post-behavior-cloning optimization, including offline RL and reward-guided approaches.
• Improve reward models and learning signals for driving policies with partner teams.
• Build robust training workflows using large-scale driving data and diagnose issues.
• Define evidence across offline metrics, simulations, and open-road evaluation.
• Productionize methods in the ML stack and lead code reviews and mentoring.

Skills

Reinforcement learning

Policy and value learning

Off-policy learning

Behaviour cloning

Python

PyTorch

Software engineering practices

Experimental judgement

Leadership ownership

Tools

C++

CUDA

Distributed training

Job description

Wayve is seeking a Senior/Staff Machine Learning Engineer in Sunnyvale to advance reinforcement learning for end-to-end driving models. You will iterate from design through large-scale experiments and integrate successful methods into driving systems.

You will lead RL work within AV Core and Core Model Safety, collaborating with researchers and engineers to push the boundaries of safe, data-driven driving policies with robust evaluation and deployment readiness.