Software Engineer, ML Infrastructure

Mission Sumary:

Our team builds the foundational infrastructure that empowers Machine Learning Engineers to develop the next generation of self-driving technology. We design and operate the high-performance, large-scale systems that process petabytes of vehicle data, run massive simulations, and train complex models. This is a software engineering role focused on building robust platforms, not an SRE position.

As an Engineer, you will be a key contributor to the team, owning the design and implementation of critical services that directly impact the pace of AV innovation.

What you'll do:

• Design, build, and deploy core components of our ML infrastructure platform on Kubernetes.
• Develop robust and scalable services that support the entire ML lifecycle, from data ingestion and processing to model training and evaluation.
• Write high-quality, maintainable code for high-throughput systems that handle petabytes of data.
• Own features and systems end-to-end, driving them from initial design through to production deployment and operation.

What we're looking for:

• 2+ years of professional software engineering experience.
• BS or MS in Computer Science or a related technical field.
• Hands-on experience developing and deploying applications on Kubernetes (k8s) is a must.
• Experience building or working on high-scale infrastructure or distributed backend systems.
• Strong proficiency in Python, Go, or a similar language.
• Solid experience with a major cloud provider (AWS, GCP, Azure).
• A strong sense of ownership and a passion for building high-quality software.

Bonus Points:

• Production experience with Ray, specifically leveraging Ray Data and Ray Train.
• Experience with GPU management or orchestration infrastructure, such as warm pools, smart scheduling, or specialized GPU frameworks.