Machine Learning Engineer - Vision Foundation Models
Foster City, CA
- Pay
USD 254,000–305,000/year — pay source
Salary 254,000 – 305,000 USD per year About Zoox
Read the full posting- 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
What you’ll work on
Full postingOwn a model area end to end, including data curation and labeling guidelines
Set quality bar using rigorous evaluation and error analysis for live operations
Deploy models under real-time and compute constraints shared with onboard perception
Turn product and safety requirements into model specs, metrics, and validation plans
From the employer’s posting
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
What you’ll bring
All qualificationsCore experience
- 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).
- Experience with in-cabin or occupant monitoring (occupant or driver monitoring systems), ideally including multi-camera or fisheye imagery and low-light conditions.
- Strong proficiency in Python and PyTorch for model design, training, and evaluation.
- Experience deploying deep learning models to real-time, resource-constrained systems (robotics, automotive, or edge devices) with TensorRT / ONNX or similar.
- Experience with vision-language models or foundation-model backbones, and with auto-labeling or synthetic data for long-tail and rare classes.
- Proficiency in C++ for model integration.
Qualification wording
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).
Experience with in-cabin or occupant monitoring (occupant or driver monitoring systems), ideally including multi-camera or fisheye imagery and low-light conditions.
Strong proficiency in Python and PyTorch for model design, training, and evaluation.
Experience deploying deep learning models to real-time, resource-constrained systems (robotics, automotive, or edge devices) with TensorRT / ONNX or similar.
Experience with vision-language models or foundation-model backbones, and with auto-labeling or synthetic data for long-tail and rare classes.
Proficiency in C++ for model integration.
Education & alternatives
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).
Tools in this posting
- C++
- Python
- PyTorch
Source — Tool mentions in context
- 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. Base Salary Range
- 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.
About Amazon
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · today
- Recorded sightings
- 2
- Last seen by us
- Oct 30, 2026
- Employer says posted
- Oct 27, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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- Check the listed location, eligibility and core experience before starting.
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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...
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Design, train, and evaluate vision models that understand passengers, objects, and behaviors inside the vehicle, across detection, pose, and action recognition.
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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
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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).
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Strong proficiency in Python and PyTorch for model design, training, and evaluation.
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Experience with vision-language models or foundation-model backbones, and with auto-labeling or synthetic data for long-tail and rare classes.
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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
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Experience with in-cabin or occupant monitoring (occupant or driver monitoring systems), ideally including multi-camera or fisheye imagery and low-light conditions.
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Experience deploying deep learning models to real-time, resource-constrained systems (robotics, automotive, or edge devices) with TensorRT / ONNX or similar.
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Proficiency in C++ for model integration.
Salary
254,000 – 305,000 USD per year
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 254,000 – 305,000 USD per year About Zoox
- Location & working pattern
Foster City, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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