Software Developer - Simulation Platform (Galileo)

General Motors•Sunnyvale, CA

1d•$104,500 - $160,200

About The Position

As a Software Engineer on the Galileo team, you will design, build, and scale the infrastructure and technology that powers testing and evaluation workflows for vehicle release and autonomous driving stack validation and verification. This includes developing and optimizing data processing pipelines, backend services, and internal tools used for large-scale analysis. In this role, you will independently own significant technical areas, drive high-quality implementation from design through production, and partner with cross-functional teams to build systems that support AV / ADAS development. You will help raise the engineering bar through sound technical judgment, strong execution, and mentorship of other engineers. The GM AV Simulation team builds world-class testing and analysis products and technologies to help accelerate development of autonomous vehicles and broader vehicle software systems. Our customers range from AV developers understanding the effects of their code on vehicle behavior, to data engineers using our pipelines for evaluation insights, to release teams tracking top-line performance metrics. AV Simulation aims to deliver intuitive user experiences for robotics and AI engineers that help move GM toward a driverless future. Galileo is building the core infrastructure and architecture to support testing at scale. As part of this team, you will help build and evolve the infrastructure required for test organization, test triggering, test analysis workflows, and related data pipelines.

Requirements

BS, MS in Computer Science, Robotics, Software Engineering, or a related field, or equivalent practical experience
Demonstrated experience building and operating high-quality production software systems
Strong proficiency in one or more programming languages such as Python, Go, JavaScript, or C++
Experience designing and building backend systems, APIs, data pipelines, or distributed systems
Solid understanding of software engineering fundamentals including testing, debugging, version control, code reviews, and system design
Experience working with cloud platforms such as AWS or GCP
Familiarity with relational databases such as PostgreSQL and analytics or warehouse technologies such as BigQuery or Redshift
Strong problem-solving, communication, and cross-functional collaboration skills
Ability to operate with ownership in a fast-paced engineering environment and drive work through ambiguity
Passion for autonomous driving technology and its potential impact on the world

Nice To Haves

Experience in robotics, AV / ADAS, simulation, or developer infrastructure
Experience building internal platforms, developer tools, or workflow orchestration systems
Experience supporting data scientists or ML / AI engineers through data pipelines and analysis workflows
Familiarity with web technologies such as Node or React
Experience improving reliability, latency, and performance in production systems
Experience developing software for high-scale or safety-critical environments
Interest in scientific analysis, large-scale evaluation, or data-driven engineering workflows

Responsibilities

Design, develop, and maintain software systems that support large-scale autonomous driving evaluation workflows
Own major components and services that enable simulation, test execution, analysis, and reporting at scale
Build and improve infrastructure used to process and analyze large volumes of driving and evaluation data
Drive reliable software delivery through strong engineering practices including code reviews, automated testing, observability, and continuous integration
Collaborate across teams to define technical requirements, resolve ambiguous problems, and deliver scalable solutions
Debug complex production issues, improve system performance, and strengthen operational excellence for critical infrastructure
Mentor other engineers and contribute to a collaborative, inclusive, and high-performing engineering culture
Support GM engineering culture through ownership, technical excellence, teamwork, and continuous improvement