Staff Software Engineer - Simulation Platform (Galileo)

General Motors•Sunnyvale, CA

2d•$185,100 - $284,100•Hybrid

About The Position

The Simulation, Evaluation, and Data organization develops the platforms, tools, metrics, and workflows that accelerate GM’s autonomous-driving mission. The VTA team builds the core infrastructure for test organization, test triggering, simulation execution, result analysis, and the data pipelines that connect these workflows. Our customers include autonomy and robotics engineers who need fast, trustworthy feedback on vehicle behavior; data engineers who build large-scale analysis workflows; and release teams that use evaluation results and performance metrics to make readiness decisions. We partner across Autonomy, Simulation, Systems Engineering, Safety, Data, and other engineering organizations to deliver intuitive, reliable, and scalable developer experiences.

Requirements

Bachelor’s degree or higher in Computer Science, Robotics, Engineering, or a related technical field, or equivalent practical experience.
7+ years of experience building and operating production software systems, platforms, or infrastructure.
Proven experience providing cross-team technical leadership, including defining strategies or architectures adopted by multiple teams.
Strong experience designing and implementing distributed systems, service-oriented or microservice architectures, and data-intensive applications.
Production programming experience in Python and at least one additional language such as Go, C++, Java, TypeScript, or a similar language.
Experience with cloud platforms and modern software delivery practices, including CI/CD, automated testing, observability, and operational excellence.
Experience building developer tools, automation, or platform capabilities that improve engineering productivity and achieve broad internal adoption.
Strong written and verbal communication skills, including the ability to explain technical decisions, communicate risk, and influence diverse stakeholders.
Demonstrated ability to work independently through ambiguity, prioritize high-leverage work, and deliver results across organizational boundaries.

Nice To Haves

Experience with autonomous vehicles, robotics, simulation, validation, evaluation, or other safety-critical or high-stakes systems.
Experience designing, running, and interpreting large-scale simulation or field experiments.
Experience with test frameworks, scenario libraries, metrics systems, release gating, or continuous evaluation pipelines.
Experience with PostgreSQL or similar relational databases and analytical technologies such as BigQuery, DuckDB, or Amazon Redshift.
Familiarity with data transformation tools such as dbt, Dataform, or SQLMesh.
Experience with ROS, Python/C++ interoperability, or modern visualization and dashboarding tools such as Streamlit or Looker.
Experience optimizing systems under significant latency, throughput, reliability, or cost constraints.
Experience developing safety-critical software or applying rigorous validation and risk-management practices.
A track record of creating reusable frameworks, libraries, or platform abstractions that enable other teams to move faster.

Responsibilities

Define and evolve the technical vision, architecture, and multi-year roadmap for Galileo and related simulation-platform capabilities.
Design and implement highly scalable systems capable of orchestrating and analyzing millions of simulation miles and large volumes of test results.
Lead cross-functional initiatives that integrate simulation, evaluation, data, and developer tooling into regular engineering and release workflows.
Build platform capabilities for test creation, test-suite management, execution orchestration, result storage, data processing, visualization, and quantitative analysis.
Establish durable architectural patterns for distributed systems, service interfaces, data-intensive workflows, and cloud-based infrastructure.
Identify and resolve bottlenecks in performance, reliability, cost, usability, and operational scalability; use measurable outcomes to guide prioritization.
Drive engineering excellence through design reviews, code reviews, automated testing, continuous integration, observability, incident learning, and clear operational ownership.
Make complex technical tradeoffs clear to stakeholders, communicate risks and dependencies, and drive decisions across organizational boundaries.
Mentor engineers and multiply team effectiveness through technical guidance, reusable patterns, documentation, and constructive feedback.
Partner with product and engineering leaders to translate customer needs into pragmatic technical strategies and deliverables.
Help define and embody GM engineering culture and principles, with a focus on customer impact, inclusion, continuous improvement, and accountability.