Zoox

About Zoox

Revolutionizing transportation with autonomous vehicle technology

🏢 Tech, Automotive👥 1001+ employees📅 Founded 2014📍 Vintage Park, Foster City, CA💰 $1.2b3.9
B2CArtificial IntelligenceCarsTransportElectric VehiclesAutomation

Key Highlights

  • Raised $1.2 billion in Series B funding
  • Headquartered in Foster City, CA with 1001+ employees
  • Innovative vehicle design with independent wheels and no front/back
  • Part of a $2 trillion industry projected by 2030

Zoox, headquartered in Foster City, CA, is pioneering autonomous vehicle technology with a unique driverless ecosystem. The company has raised $1.2 billion in Series B funding and employs over 1,000 people. Its innovative vehicle design, revealed in December 2020, features independent wheels and a b...

🎁 Benefits

Zoox offers work-from-home opportunities, comprehensive health insurance, and generous paid parental leave. Employees enjoy unlimited flexible paid ti...

🌟 Culture

At Zoox, the culture is centered around innovation in autonomous transportation, with a focus on safety and enjoyment. The company promotes a collabor...

Overview

Zoox is hiring a Software Engineer for their ML Platform team to enable machine learning use cases for autonomous driving. You'll work with technologies like Python and various ML frameworks. This position requires experience in machine learning and software development.

Job Description

Who you are

You have a strong background in software engineering with a focus on machine learning applications — your experience includes developing and deploying ML models that enhance autonomous driving capabilities. You are proficient in Python and have hands-on experience with deep learning frameworks, enabling you to contribute effectively to the ML Platform team at Zoox.

You understand the intricacies of machine learning infrastructure and have worked with tools like MLflow and Kubernetes — your knowledge allows you to streamline the process from ideation to productionization of AI innovations. You thrive in collaborative environments, working closely with cross-functional teams to meet the needs of both vehicle and ML teams.

You are passionate about pushing the boundaries of machine learning practices — your curiosity drives you to explore new ML domains and technologies that can enhance the capabilities of autonomous systems. You are eager to learn and grow as Zoox expands its robotaxi deployments.

What you'll do

In this role, you will enable various ML use cases for autonomous driving, including scene understanding and automated mapping — your contributions will directly impact the efficiency and effectiveness of the ML tools used by applied research teams. You will collaborate with teams across perception, behavior ML, simulation, and data science to ensure that the ML infrastructure meets the evolving needs of the organization.

You will play a crucial role in building and operating the base layer of ML tools and inference libraries — your work will help reduce the time it takes to bring cutting-edge AI innovations from concept to reality. You will also coordinate with the Advanced Hardware Engineering group to specify the next generation of autonomous hardware, ensuring seamless integration with ML systems.

As part of the ML Platform team, you will have the opportunity to mentor junior engineers and contribute to the growth of the team — your insights and expertise will help shape the future of autonomous driving technology at Zoox.

What we offer

At Zoox, you will be part of a mission-driven team focused on reimagining transportation through innovative technology — we offer a collaborative work environment where your contributions will have a significant impact. You will have access to professional development opportunities as we expand our robotaxi deployments and venture into new ML domains.

We encourage you to apply even if your experience doesn't match every requirement — we value diverse perspectives and are committed to building a team that reflects the communities we serve. Join us in our mission to create safe, reliable, and enjoyable autonomous transportation for everyone.

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