Zoox
Senior / Staff Machine Learning Engineer - Behavior Models for Road Users
Foster City, CA · On-site · Senior
- Discipline
- Software
- Industry
- Automotive
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
Software
Senior / Staff ML Engineer focusing on behavior models for road users, delivering ML pipelines and models to predict agent behavior and support planning for the ego vehicle within Zoox's Offline Driving Intelligence program.
Required
- machine learning
- behavior models
- road users
- simulation
- training pipelines
- validation
- driving stack
- predictive modeling
Preferred
- reinforcement learning
- simulation environments
- autonomous driving
- ML Ops
- data pipelines
- model deployment
Employer description
This role in the Offline Driving Intelligence team is responsible for developing/learning behavior models for road users such as cars, bicycles, and pedestrians. These agents populate Zoox’s simulations and must be indistinguishable from real road users, yet fully controllable: promptable into the rare, adversarial, safety-critical behaviors we need to test against. This means the team’s models directly impact how fast Zoox can train, validate and ship its driving stack. Our team collaborates closely with Planner, Simulation and Validation teams to develop and validate our driving performance. As an ML Agents Machine Learning Engineer, you will work on the bleeding edge of the industry, developing novel machine learning pipelines and models to predict the behavior of other agents in the world and planning the best course of action for the ego vehicle.
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