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Machine Learning Engineer - Vision Foundation Models

Zoox

CAFull-time$254–305K/yrPosted 1w agoStill listed 4 days ago

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At a glance

Compensation
$254–305K/yr
Location
CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Machine Learning Engineer will develop vision-based in-cabin perception models that recognize passengers, objects, and behaviors in Zoox robotaxis. The role owns a model area from data curation and training through evaluation and deployment, with attention to real-time and compute constraints. The work supports rider safety and operations and involves collaboration with product, operations, safety, and vehicle software teams.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningComputer VisionDeep LearningPython (Programming Language)PyTorch (Machine Learning Library)Data CurationModel ValidationObject DetectionActivity RecognitionC++ (Programming Language)Pose RecognitionAction RecognitionFine-Grained ClassificationConvolutional DetectorsVision-Transformer DetectorsSelf-Supervised BackbonesFoundation-Model BackbonesVision-Language ModelsAuto-LabelingSynthetic DataDataset CurationLabeling GuidelinesMetric DesignError AnalysisOccupant MonitoringMulti-Camera ImageryFisheye ImageryLow-Light ImagingReal-Time Model DeploymentTensorRTONNX

Qualifications

MS or PhD in CS, ML, CV or Related6+ Years Industry ExperiencePhD With 3+ Years Experience

Benefits

Paid Time Off
Medical Insurance

Full job description

The Perception team at Zoox is responsible for how our purpose-built robotaxi understands the world, including what happens inside the cabin. In this role, you will design, train, and evaluate vision-based in-cabin perception models that understand passengers, objects, and behaviors inside the vehicle. These models support rider safety and the operations that keep each ride running smoothly. You will independently own a model area end to end, from data curation and training through evaluation and deployment under real-time and compute constraints, working closely with partners across the company. Your work has a direct impact on rider safety and experience as Zoox scales its robotaxi service.

In this role, you will...

  • Design, train, and evaluate vision models that understand passengers, objects, and behaviors inside the vehicle, across detection, pose, and action recognition.

  • Independently own a model or feature area end to end: curate data, define labeling guidelines, train and evaluate models, and take them through deployment.

  • Set the quality bar for the models you own, using rigorous evaluation and error analysis so they are reliable enough to support live operations.

  • Deploy models under real-time and compute constraints shared with the rest of the onboard perception system.

  • Partner across product, operations, safety, and vehicle software to turn requirements into model specifications, metrics, and validation plans.

Qualifications

  • MS or PhD in Computer Science, Machine Learning, Computer Vision, or a related field with 6+ years of industry experience (PhD with 3+ years).

  • Deep expertise in computer vision and deep learning for image and video understanding: object detection, pose and action recognition, and fine-grained classification, with hands-on experience with modern architectures (convolutional and vision-transformer detectors, and self-supervised or foundation-model backbones such as DINOv3).

  • Strong proficiency in Python and PyTorch for model design, training, and evaluation.

  • Experience with vision-language models or foundation-model backbones, and with auto-labeling or synthetic data for long-tail and rare classes.

  • Track record of owning the full ML lifecycle on real-world data: dataset curation and labeling guidelines, training, metric design (precision, recall, and false-positive rate at an operating point), and error analysis.

Bonus Qualifications

  • Experience with in-cabin or occupant monitoring (occupant or driver monitoring systems), ideally including multi-camera or fisheye imagery and low-light conditions.

  • Experience deploying deep learning models to real-time, resource-constrained systems (robotics, automotive, or edge devices) with TensorRT / ONNX or similar.

  • Proficiency in C++ for model integration.

About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

Follow us on LinkedIn

Accommodations If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

254000 - 305000 USD a year

Base Salary Range

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.

How this job compares

Set against the 6,278 open Machine Learning Engineer jobs on Olive Jobs, counted November 9, 2026.

Pay
  • This posting$254–305K/yr
  • California median$180–263K/yr1,462 salary ranges
  • US median$150–246K/yr5,126 salary ranges

This range's midpoint, $280K, is 24% above the California median midpoint ($225K) — in the top quarter of Machine Learning Engineer salary ranges in California.

Openings
Olive Jobs lists 1,939 open Machine Learning Engineer jobs in California and 6,278 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 3 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,993 postings).
Education
2,037 of the 6,278 open Machine Learning Engineer jobs (32%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 9, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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