Senior / Staff Machine Learning Engineer - Perception Attributes

Reposted 7 Days Ago
Foster City, CA, USA
Hybrid
242K-333K Annually
Senior level
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
Zoox is an autonomous mobility company that’s created a purpose-built robotaxi to give the world a better way to ride.
The Role
The role involves developing and maintaining behavioral models for road users to enhance autonomous vehicle decision-making, collaborating with other teams and optimizing outputs for safety and effectiveness.
Summary Generated by Built In

As a machine learning engineer within the Attributes team in the Perception department, you will take ownership of developing and enhancing sophisticated behavioral models for various road users, including vehicles, pedestrians, and cyclists. Your work will focus on creating and maintaining robust perception attribute models that generate critical signals for our autonomous driving stack. These signals are essential inputs that enable our Prediction and Planning teams to make intelligent, safe driving decisions for our autonomous vehicles. 

The Attributes team is fundamental to Zoox's autonomous driving capabilities. The models you develop will serve as the foundation for how our vehicles understand and interact with other road users, directly contributing to the safety and effectiveness of our autonomous driving system. By creating reliable and accurate behavioral models, you enable Zoox's vehicles to make smart, safe decisions in complex urban environments, bringing us closer to our goal of revolutionizing urban mobility.

In this role, you will...

  • Lead the development of sophisticated behavioral models for vehicles, pedestrians, and cyclists as a key member of the Attributes team within Zoox's Perception department.
  • Create and maintain perception attribute models that generate essential signals, enabling our autonomous vehicles to understand and predict the behavior of various road users.

  • You will collaborate closely with Prediction and Planning teams to optimize your models' outputs, directly influencing how our autonomous vehicles make real-time driving decisions.

  • Work with data labeling and ontology teams on data labeling and ontology definitions of the road users in different attributes and generate auto-labeling or data mining strategies for different attributes. 

  • You will help shape the future of autonomous mobility by bridging the critical gap between raw perception data and autonomous decision-making.

Qualifications:

  • MS/PhD in computer science or related fields with a minimum of 7 years of relevant experience

  • Experience with training and deploying Deep Learning models

  • Experience with knowledge distillations from large foundation models

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

  • Fluency programming in Python and extensive experience with algorithm design

  • Strong mathematics skills

Bonus Qualifications

  • Familiarity of VLMs/VLAs/ViTs

  • Experience with large model distillation in a production environment 

  • Familiarity with C++

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.

Skills Required

  • MS/PhD in computer science or related fields
  • Minimum of 7 years of relevant experience
  • Experience with training and deploying Deep Learning models
  • Experience with production Machine Learning pipelines
  • Fluency programming in Python
  • Strong mathematics skills

Zoox Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zoox and has not been reviewed or approved by Zoox.

  • Healthcare Strength Healthcare is extensive, with broad medical and vision options, company‑paid disability coverage, and multiple mental‑health resources. Feedback suggests coverage breadth and auxiliary programs support a wide range of needs.
  • Parental & Family Support Family supports include paid parental leave, additional pregnancy disability time, fertility coverage, and adoption/surrogacy assistance. Backup care and family‑oriented programs further reinforce support across life stages.
  • Wellbeing & Lifestyle Benefits Day‑to‑day perks are robust, including free daily meals, fitness subsidies, commuter support, and on‑site amenities. Feedback suggests these lifestyle benefits enhance convenience and workplace experience, especially for office‑based roles.

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The Company
HQ: Foster City, CA
2,900 Employees
Year Founded: 2014

What We Do

Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.

Why Work With Us

At Zoox, we are working to solve one of the greatest technological challenges of our generation. From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.

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