Senior Software Engineer - Autonomy Evaluation

Description

The Role:

General Motors is a global leader in advanced driver assistance. With Super Cruise hands-free technology in more than 500,000 Super Cruise-equipped vehicles on the road, and over 700 million hands-free miles driven, GM is proving that automation can be trusted, intuitive, and helpful. GM has the global reach to bring cutting-edge advances to everyday drivers at an unprecedented scale. Join us to help deliver the next generation of safe and delightful personal autonomous vehicle experiences.

About the Organization:

The Evaluation team builds and evolves the evaluation ecosystem that powers developing and scaling GM's autonomous driving technology. We develop metrics, automated workflows, and analysis approaches that enable data-driven decisions across AV development and verification. Partnering with Autonomy, Simulation, Systems, and Safety teams, we act as system-level integrators and arbiters of end-to-end AV quality. We own large scale test scenario libraries, continuous evaluation pipelines, and critical risk assessment and release gating components, treating road testing, data mining, training, and metrics as first-class use cases in a unified analytics framework. By joining this team, you will help shape GM's core evaluation platforms, turn system-level results into clear feedback, and help accelerate validated AV deployment at scale.

What You'll Do

• Design and implement analysis algorithms that summarize, aggregate, and cluster metrics produced by simulations of the autonomy stack

• Build and maintain GM's primary autonomy evaluation dashboards and reports that provide clear, explainable insights to engineering and leadership, including trend analysis, drift detection, and scenario coverage.

• Leverage vision-language models (VLMs) and large language models (LLMs) to classify autonomy performance, critical scenarios, and prioritize validation efforts, integrating human-in-the-loop where appropriate.

• Maintain a high technical standard through architectural design, code reviews, and by following software-engineering best practices.

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

• 3+ years applied experience in data analysis, ML evaluation, or autonomy analytics, working with large-scale datasets and statistical methods.

• Proficiency with Pandas, NumPy, SciPy, and plotting/visualization libraries.

• Bachelor's or higher degree in Computer Science, Data Science, Mechanical or Aerospace Engineering, or equivalent practical experience.

• A strong understanding of how to visualize quantitative information effectively and transparently. The ability to decompose a multi-dimensional space into something consumable.

• Experience evaluating robotics systems or autonomous vehicles, including sensor data (camera, lidar, radar) and time-series analysis.

• A strong curiosity to question anomalous data and root-cause discrepancies