Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.
Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. You will be part of an organization with strong leadership and a transparent, respectful culture that enables you to reach your full potential.
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.
In this role, you will:
Generate test sets of driving logs to evaluate the performance of the autonomous driving system
Validate and optimize the test sets to ensure they meet requirements and reflect the statistical distribution of our targeted robotaxi service.
Collaborate with cross-functional stakeholders to gather requirements and integrate test sets with our testing frameworks
Develop and maintain data pipelines and tools for efficient test set creation and management
Define and document best practices for the design, curation, and maintenance of large-scale test sets
Present findings and test-set characteristics to both technical and non-technical audiences to inform system development
Qualifications
Master's Degree in Data Engineering, Data Science, Quantitative Science or a related field and at least 3 years of relevant industry experience or PhD in Data Engineering, Data Science, Quantitative Science or a related field
Proficiency in Python for data analysis and scripting
Experience building and curating large test sets for statistical studies or performance analysis
Strong communication and collaboration skills for working with cross-functional teams
Bonus Qualifications
Experience with PySpark
Experience with big data platforms such as Databricks or AWS EMR
Professional experience in the autonomous driving domain
