Machine Learning Engineer - ML Agents and Planning

Foster City, CA hybrid Until 9/22/2026 5+ years exp H-1B sponsor history First posted July 24, 2026 Last posted July 24, 2026
Job description
The Offline Driving Intelligence team is responsible for developing Foundation Models for ML Agents and planning, applying them off-vehicle to provide generalization capabilities to simulation and validation. Our team collaborates closely with the Planner, Simulation and Validation teams to develop and validate our driving performance. As an ML Agents and Planning 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.

In this role, you will...

  • You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like agents.
  • You will work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
  • You will contribute to our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
  • You will develop metrics and tools to analyze errors and understand improvements of our systems
  • You will collaborate with engineers on Perception, Planning,Simulation, and Validation to solve the overall Autonomous Driving problem.

Qualifications

  • PhD degree in computer science or related field or master's degree and 5+ years of professional experience in a relevant field.
  • Experience in Planning and / or Prediction using Reinforcement Learning techniques 
  • Experience with training and deploying transformer-based model architectures
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Fluency in Python with a basic understanding of C++

Bonus Qualifications

  • Top tier publications (NeurIPS, ICML, CVPR)
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

Compensation (from employer):
189000–270000 USD per year

About this role

Summary

Develop ML models for autonomous vehicle planning, prediction, simulation, and validation.

Job title

Machine Learning Engineer - ML Agents and Planning

Experience level

5+ years

Minimum experience

5+ years exp

Industry

automotive

Location requirements

Foster City, CA; remote work not specified

Salary

$189k–$270k

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

pythonC++transformer modelsmachine learning pipelinesreinforcement learning

Preferred skills

publicationsneural networks

Specializations

machine learningreinforcement learningdeep learningplanningprediction
Locations

Structured locations inferred from the posting.

Foster City, CA, USA

Hybrid City