Senior ML Engineer — Learned Driving Policies

Neura Market; Mountain View, Northern (CA, KY); Hybrid; USD 213,000 - 263,000; Full time

Job summary

Waymo is seeking an Autonomy MLE in Mountain View for a hybrid role that bridges perception and planning to train, evaluate, and release production-ready driving policies for robust, safe autonomous navigation.

You will collaborate across perception and planning teams, deploy models into closed-loop simulators, and drive the transition to data-driven policies with safety metrics and production readiness.

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 with RL/ imitation learning.
• Familiarity with Vision-Language-Action (VLA) models and World Models is a strong plus.

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 and drive transitions into production releases.
• Advance the transition from rule-based heuristics to scalable, data-driven learned policies.

Skills

ML models

Reinforcement learning

Imitation learning

PyTorch

JAX

closed-loop simulation

production deployment

Tools

PyTorch

JAX

Job description

Waymo is seeking an Autonomy MLE in Mountain View for a hybrid role that bridges perception and planning to train, evaluate, and release production-ready driving policies for robust, safe autonomous navigation.

You will collaborate across perception and planning teams, deploy models into closed-loop simulators, and drive the transition to data-driven policies with safety metrics and production readiness.