Senior Software Engineer, ML Infrastructure

Motional•Pittsburgh, PA

2d•Hybrid

About The Position

Mission Summary: 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 a Senior 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.

Requirements

4+ 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.

Responsibilities

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.