Role: As a Staff Software Engineer on the Metrics Frameworks team within the Simulation, Evaluation, and Data organization, you will provide technical leadership for the infrastructure and frameworks that accelerate autonomous vehicle development, testing, and deployment. You will drive the design, evolution, and scalability of specialized analytics platforms and developer tooling that enable internal teams to build robust quantitative analysis pipelines and define high-quality metrics at scale.
In this role, you will influence architecture, raise engineering standards, and lead the delivery of shared systems that support feature design, prioritization, validation, and post-launch performance evaluation. The analytics framework you help shape will power road event monitoring, data mining and training workflows, and simulation-based metrics, directly contributing to GM’s safe, scalable, and high-performing driverless technology.
About the Organization: The Simulation, Evaluation, and Data organization is dedicated to advancing autonomous vehicle development through cutting-edge simulation and evaluation technologies. Within this organization, the Metrics Frameworks team is responsible for building, maintaining, and evolving the analytics foundation that supports GM’s autonomous driving goals.
The team delivers robust, scalable, and high-leverage tools that enable data-driven decision-making across the AV feature development lifecycle. We partner closely with Simulation Evaluation, Embodied AI, and Systems and Test Engineering to improve engineering velocity and effectiveness through automation, shared libraries, and common infrastructure. We are accountable for the performance, reliability, and scalability OKRs of the analytics framework, including the development of customized analytics workflows, operational telemetry, and KPI dashboards that inform prioritization and execution.
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Lead the technical vision, architecture, and roadmap for tooling that aggregates signals across simulation, road, and other data sources, enabling users to build scalable quantitative analysis pipelines and extract actionable insights with minimal friction
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Design and deliver high-impact automation tools that improve team productivity across test creation, data collection, analysis, debugging, and performance monitoring
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Strong proficiency in C++ and Python in production environments, including software design, unit testing, code review, and performance tradeoff analysis
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Proven experience developing scalable software platforms or evaluation frameworks, ideally for autonomous vehicles, robotics, or other complex data-intensive systems
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BS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or a related technical field
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Strong organizational, collaboration, and communication skills, with the ability to influence across technical teams
