Senior / Staff Machine Learning Engineer - Scene Intelligence
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ining, auto-labeling, and dataset construction to power our ML flywheel Lead the full post-training stack for VLMs and VLAs, including C ontinual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following. Utilize our large-scale data pipelines and ML infrastructure to resea
Supports OPT
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The job
Location
Foster City, CA
Work setting
Hybrid
Hours per week
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Experience required
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New graduates accepted
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Skills mentioned
Compensation & benefits
Pay range
$199,000–$305,000/yr
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Verified live
Last checked
Sept. 23, 2026, 3:45 a.m.
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Employer
Company
Zoox
Industry
Technology / Software
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ghly 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 per
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Zoox
Full description
The Perception team at Zoox creates the "eyes and ears" of our self-driving robots. Navigating safely and efficiently in complex environments requires detecting, classifying, tracking, and understanding various attributes of surrounding objects—all in real-time and with exceptional accuracy.
As an engineer in the Scene Understanding team, you will develop advancedVision-Language-Action (VLA) models that perceive our vehicle's surroundings to identify hazards and make driving suggestions. You will utilize VLA models for detecting rare events and ensuring safe driving in these situations. You'll work with state-of-the-art machine learning models that operate in real-time on our robotaxi platform with minimal latency. Collaborating with world-class engineers and researchers across sensors, planning, and other teams, you'll have access to premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions.
In this role, you will...
Design and train Vision-Language-Action (VLA) solutions for robotaxis
Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel
Lead the full post-training stack for VLMs and VLAs, including
C
ontinual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following.
Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior
Partner with cross-functional teams to integrate perception signals
Qualifications
MS or PhD in Computer Science or related field
Background in deep learning solutions for VLM and VLA models
Track record in post-training large-scale models, CPT, SFT, RL
Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics
Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM)
Bonus Qualifications
Deep knowledge of cutting-edge computer vision techniques
Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
Experience with integrating large language models to various tasks.
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.
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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.
Eligibility signals are matched from the employer's own wording and shown with the source text so you can check them. A blank field means the posting did not say — not that the answer is no.
This is informational only and is not immigration advice. Confirm your work authorization with your DSO before accepting any role.