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Senior / Staff Machine Learning Engineer - Behavior Models for Road Users

Foster City, CA

Pay
USD 254,000–366,000/yearLocation-specific pay — pay source
Salary 254,000 – 366,000 USD per year 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.
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Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
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What you’ll work on

Full posting
  • Develop imitation and reinforcement learning models that generate human-like driving plans

  • Build generative behavior models conditionable on scenario intent for stress-testing

  • Estimate driving plan quality across safety, progress, comfort and realism

  • Develop metrics and tools to analyze errors and track system improvements

From the employer’s posting
Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents.
Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent
Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.
Develop metrics and tools to analyze errors and understand improvements of our systems.

What you’ll bring

All qualifications

Core experience

  • Experience in one of the following: Planning, Prediction, Reinforcement Learning, Imitation Learning, generative modeling (diffusion, autoregressive models)
  • Experience with training and deploying transformer-based model architectures
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Qualification wording
Experience in one of the following: Planning, Prediction, Reinforcement Learning, Imitation Learning, generative modeling (diffusion, autoregressive models)
Experience with training and deploying transformer-based model architectures
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Education & alternatives
Qualifications - PhD degree in computer science or related field and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience - Experience in one of the following: Planning, Prediction, Reinforcement Learning, Imitation Learning, generative modeling (diffusion, autoregressive models)

Tools in this posting

  • C++
  • Python
Source — Tool mentions in context
- Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines - Fluency in Python ML frameworks and a basic understanding of C++ Bonus Qualifications

Posting record

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Open 6 monthsWe first saw this posting 197 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 15, 2026 · 197 days ago
Recorded sightings
318
Last seen by us
Oct 30, 2026
Employer says posted
Dec 17, 2025

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

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.

In this role, you will...

  • Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents.

  • Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism.

  • Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent — "cut off the ego vehicle," "jaywalk here" — for targeted stress-testing.

  • Leverage our compute, infrastructure and large corpus of data to push boundaries of the field.

  • Develop metrics and tools to analyze errors and understand improvements of our systems.

  • 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 and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience

  • Experience in one of the following: Planning, Prediction, Reinforcement Learning, Imitation Learning, generative modeling (diffusion, autoregressive models)

  • Experience with training and deploying transformer-based model architectures

  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines

  • Fluency in Python ML frameworks and a basic understanding of C++

Bonus Qualifications

  • Top tier publications (NeurIPS, ICML, CVPR)

  • Experience with JAX

Salary

254,000 – 366,000 USD per year

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.

Employment type

Full-time

Source details

View original posting ↗

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Pay
Salary 254,000 – 366,000 USD per year 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.
Location & working pattern

Foster City, CA

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