Senior Software Engineer - Controls Metrics

Number of employees

4100

Foster City, CA, United States

Posted on: 2025-09-18

Category: emobility

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Employment type:

Full time

Experience required:

Senior

Salary

Salary not provided

About the company:

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 looking for a controls metrics engineer to join our Planning and Control team. The controls team is responsible for our vehicle’s longitudinal and lateral dynamics. As Zoox moves towards deploying vehicles at scale we need a controls engineer to monitor and optimize fleet wide performance of the system.

In this role, you will:

  • You will define key performance metrics for our safety critical control system  in order to guide product development to a commercial launch
  • You will work closely with software engineers, data engineers, and data scientists to develop metrics and tools for analyzing errors and guiding improvements in our systems
  • You will apply distributed computing algorithms to efficiently analyze petabytes of urban driving data
  • You will contribute to the refinement and optimization of the control system
  • You will contribute to all phases of the software development cycle
  • Qualifications

  • BS or MS degree in Computer Science, Electrical Engineering, Mechanical Engineering, Data Science, or related field Statistics, Computer Science, Machine Learning, Applied Mathematics, or related quantitative field
  • Strong programming skills in C / C++ and Python
  • Strong background in controls (PID, LQR, MPC, etc.) for complex dynamic systems
  • Strong background in statistics, mathematical, and geometrical skills
  • Understanding of vehicle dynamics and automotive sensors and actuators
  • Bonus Qualifications

  • PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or related field
  • Experience with designing metrics and delivering actionable insights that drive business decisions
  • Experience with large-scale data analysis and statistical modeling as well as hands-on experience with production machine learning pipelines (including dataset creation, training frameworks, and metrics pipelines)
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