Staff Engineer • Lead

Who you are

You have a strong background in software engineering with a focus on machine learning and performance optimization — your experience includes leading initiatives that enhance the efficiency of ML platforms. You are well-versed in deep learning frameworks and have a solid understanding of computer vision applications, particularly in the context of autonomous systems. Your leadership skills enable you to guide a team of engineers effectively, fostering collaboration and innovation.

You thrive in environments where you can push the boundaries of technology — your passion for autonomous driving and robotics drives you to explore new ML domains and improve existing systems. You possess excellent problem-solving skills and can communicate complex technical concepts to diverse audiences, ensuring alignment across teams.

What you'll do

In this role, you will lead the ML Performance Optimization initiatives at Zoox, working closely with various teams including Perception, Prediction, and Planning. Your primary responsibility will be to enhance the Training and Inference platform, making it as fast and efficient as possible for autonomous driving applications. You will collaborate with applied research teams to develop and operate the foundational ML tools and frameworks that support in- and off-vehicle use cases.

You will also mentor and guide a team of software engineers, acting as a force multiplier for internal customers. As the team expands with the growth of robotaxi deployments, you will have the opportunity to influence the direction of ML practices within the organization. Your contributions will directly impact the safety and reliability of autonomous transportation solutions.

What we offer

At Zoox, you will be part of a mission-driven team dedicated to reimagining transportation through innovative technology. We offer a collaborative work environment where your ideas and contributions are valued. You will have access to cutting-edge tools and resources to support your work in machine learning and autonomous systems. We encourage you to apply even if your experience doesn't match every requirement, as we believe diverse perspectives lead to better solutions.