Senior ML Engineer, Autonomous Driving Policy & Behavior

Waymo; Mountain View (CA); Hybrid; USD 213,000 - 263,000; Full time

Benefits offered by this job

Discretionary annual bonus

Equity incentive plan

Benefits program

Job summary

Waymo in Mountain View is seeking an Autonomy MLE to bridge perception and planning and to develop and release robust learned driving policies. This hybrid role reports to the Technical Lead Manager and focuses on training, evaluating, and transitioning production-ready decision-making models into real-world autonomous navigation systems.

You will work across perception and planning stacks, deploy models into simulation, and drive the transition from rule-based heuristics to data-driven

Qualifications

• 2-5+ years experience training and releasing ML models in autonomous driving, robotics, or complex spatial AI.
• Hands-on experience across perception and planning stacks; proficiency in learned driving policies (RL / imitation learning), PyTorch / JAX, closed-loop simulator evaluation, and production releases.
• Familiarity with Vision-Language-Action (VLA) models and World Models is a strong plus.
• Experience using foundation models and AI tools for scenario generation, evaluation analysis, and rapid experimentation.

Responsibilities

• Develop, evaluate, and release learned driving policies for complex navigation and yielding scenarios.
• Work cross-functionally at the intersection of perception and planning, translating multi-modal perception outputs into robust behavioral actions.
• Deploy learned models into closed-loop simulation environments, benchmark against safety metrics, and drive production releases.
• Advance the transition from rule-based heuristics to scalable, data-driven learned policies.

Skills

ML model development

Perception & planning

RL / imitation learning

PyTorch / JAX

Closed-loop simulation

Production deployment

Vision-Language-Action (VLA)

World Models

Foundation models for scenario gen

Tools

PyTorch

JAX

Job description

Waymo in Mountain View is seeking an Autonomy MLE to bridge perception and planning and to develop and release robust learned driving policies. This hybrid role reports to the Technical Lead Manager and focuses on training, evaluating, and transitioning production-ready decision-making models into real-world autonomous navigation systems.

You will work across perception and planning stacks, deploy models into simulation, and drive the transition from rule-based heuristics to data-driven