Job Description

Role Overview:

As a Senior Software Simulation Validation Engineer, you will be a technical leader responsible for ensuring the quality and reliability of autonomous vehicle simulation platforms. The role bridges hands-on coding, protocol/process definition, integration of metrics, and automated regression monitoring — all foundational to verifying the performance, fidelity, and validity of highly complex simulation systems. This position will follow both collaborative and technical standards with an emphasis on scalable, maintainable, and programmatic approaches.

About the organization

The GM Advanced Driver-Assistance Systems (ADAS) team develops and delivers intelligent, safety, and convenience features to elevate every driver’s experience. By integrating state-of-the-art sensing, perception, and control technologies, GM ADAS empowers vehicles with cutting-edge capabilities. Our cross-functional experts collaborate to design scalable, reliable systems that set new standards for automotive innovation and make mobility easier, safer and more convenient for all.

The Sim Validation team at GM ensures our simulation environments accurately mirror real-world driving conditions and sensor interactions. On the one hand, by measuring and monitoring the realism, accuracy, and coverage of our virtual environments and sensor models, Sim Validation enables developers and engineers to validate autonomous and ADAS technologies with greater realism and confidence. On the other hand, our validation methodologies establish a basis of trust in our simulation results and capabilities when reporting to executives and regulatory bodies. Our solutions reduce reliance on physical testing, streamline development, and provide essential insights that guide safer, more robust vehicle systems.

What you and your team will be doing

• Build and maintain simulation fidelity and validity metrics, quantifying the gap between simulation and road in novel ways. Construct mechanisms to attribute issues to components of simulation systems.

• Design and maintain robust data ingestion and loading tools to support diverse simulation pipelines

• Develop and optimize nodes in both C++ and Python to extract and aggregate metric outputs at scale.

• Create, maintain, and monitor test suites, enabling automated regression detection. Debug, track, and report on validity measures, including deep root-cause analysis. Triage and aid in the prioritization of resolving validation issues.

• Contribute documentation in the form of technical designs, experiment results and internal publications.

• Conduct code reviews and assist teammates in tracking evolving requirements and user workflows.

• Interface with cross-org partners to articulate requirements, resolve handoff issues, and share best practices.

Required Skills & Qualifications:

• 3+ years of experience writing Python in a production environment (unit testing, code review, algorithm performance and tradeoffs, etc.). Demonstrated experience with C++.

• Familiarity with data analysis, e.g. statistics

• Familiarity with SQL, ROS, numpy & scipy, and plotting/visualization libraries

• Excellent communication skills and ability to work independently, driving technical advances.

• BS in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering or similar experience.

Bonus points

• Experience building algorithms central to data analysis of engineering domains

• Experience developing software solutions that are used across engineering teams

• Experience with computational geometry, linear algebra, or Machine Learning

• Experience with time-series data analysis and online performance monitoring tools

• Experience in simulation/test engineering or automotive autonomy platforms

• Experience automating pipelines, maintaining and troubleshooting test protocols.

• Familiarity with some of Google Cloud, Big Query, containerized builds, large-scale continuous integration/monitoring or Python/C++ interoperability

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