Job Description
The Perception team at Zoox is fundamental to our autonomous vehicle technology, creating the understanding of the world for our self-driving robots. We enable safe and efficient navigation in complex environments through sophisticated detection, classification, and tracking systems.
As a Machine Learning Engineer on the Attributes team within 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. In this role, you will bridge the crucial gap between raw perception data and autonomous decision-making, working closely with cross-functional teams to optimize model outputs and enhance our system's overall perception capabilities. Your contributions will directly impact the safety and effectiveness of Zoox's autonomous vehicle platform, advancing our mission of revolutionizing urban mobility.
Qualifications
- MS/PhD in Computer Science or related fields with a minimum of 5 years of relevant experience
- Experience with training and deploying Deep Learning 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
Responsibilities
- You will 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 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.
- You will 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. This will directly influence how our autonomous vehicles make real-time driving decisions and bridge the critical gap between raw perception data and autonomous decision-making.
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.
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.
Responsibilities
Responsibilities
- You will 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 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.
- You will 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. This will directly influence how our autonomous vehicles make real-time driving decisions and bridge the critical gap between raw perception data and autonomous decision-making.
Requirements
Qualifications
- MS/PhD in Computer Science or related fields with a minimum of 5 years of relevant experience
- Experience with training and deploying Deep Learning 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
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