Senior​/Machine Learning Engineer - Perception Attributes

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.

• 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.
• 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.
• Help shape the future of autonomous mobility by bridging the critical gap between raw perception data and autonomous decision‑making.

• 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

• Familiarity of VLMs/VLAs/Vi Ts
• Experience with large model distillation in a production environment
• Familiarity with C++

$242,000 - $333,000 a 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.

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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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.