Manager, AV Planner Evaluation

General Motors • Sunnyvale, CA

3d • $218,800 - $335,300 • Hybrid

About The Position

As Engineering Manager for Planner Evaluation, the role is a senior contributor in GM’s Motion Planning team. The team develops metrics, automated workflows, and analysis approaches to enable data-driven decisions across autonomy development and verification. The manager leads a team with deep expertise in simulation and on-road evaluation workflows used to advance GM’s Super Cruise portfolio. The role defines the technical vision and multi-quarter roadmap for Planner Evaluation, drives design quality from architecture through validation, and aligns multiple teams to deliver reliable, scalable evaluation solutions that meet Super Cruise program goals.

The position is hybrid and requires reporting to Sunnyvale, California at least three times per week, or at another frequency dictated by the business. The salary range is $218,800–$335,300, with an incentive pay program based on company performance, job level, and individual performance. The role may be eligible for relocation benefits. Following a motor vehicle report review, the employee may be eligible to participate in GM’s company vehicle evaluation program; participants must purchase or lease a qualifying GM vehicle every four years, subject to limited exceptions.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Engineering, Machine Learning, Data Science, or a related field.
• At least 5 years of experience in engineering analysis, ML evaluation, or autonomy analytics.
• At least 3 years of experience evaluating dynamic systems using numerical and/or ML approaches, including time-series data and state derivatives.
• At least 3 years of experience building and managing high-performing engineering teams.
• Strong proficiency developing Python in production team environments, including testing, performance, and code review.
• Comfort working with C++ codebases, including reading, debugging, and instrumenting core algorithms.
• Strong hands-on familiarity with data visualization libraries for large-scale analysis and reporting.
• Demonstrated technical leadership, including driving architectural decisions, influencing cross-team designs, and owning complex services or platforms end-to-end.
• Strong cross-functional communication and ability to convert ambiguous evaluation needs into clear technical plans.
• Strong analytical curiosity and a disciplined approach to root-causing anomalous data and system discrepancies.
• Passion for self-driving technology and its potential impact on the world.

Nice To Haves

• Solid understanding of vehicle dynamics.
• Expertise in Planning and Controls system design.
• Experience evaluating robotics or AV systems using sensor data such as camera, lidar, and radar, and working with large-scale time-series analysis.
• Strong intuition for data visualization and ability to turn high-dimensional metrics into clear, trustworthy views for technical and non-technical audiences.
• Familiarity with statistical modeling, experimental design, and hypothesis testing for autonomy or simulation evaluation.
• Proficiency in SQL and experience shaping logging, data schemas, and evaluation pipelines for large-scale autonomy testing and performance monitoring.
• Experience with ROS or similar robotics/IPC frameworks, log pipelines, and experiment databases or evaluation platforms.
• Prior experience with computational geometry, linear algebra, PyTorch, and ML techniques applied to perception, prediction, planning, or control.
• Background contributing to release gating, risk assessment, and safety-related decisions for autonomy systems.
• Experience using AI-assisted development and analytics tools to improve engineering productivity and evaluation coverage.
• A background in robotics or the AV/ADAS industry.

Responsibilities

• Own multi-quarter roadmap designs and their realization for autonomy planner evaluation.
• Guide developers through system design and implementation.
• Establish verification and validation strategies for autonomy planning systems, including simulation and on-road testing.
• Partner with Safety, Systems Engineering, and Product to generate requirements for onboard systems.
• Lead root-cause investigations for complex integration issues using data-driven techniques and principled experimentation.
• Create test plans for new features and define useful metrics for analyzing performance.
• Mentor engineers across teams, raising technical judgment, design quality, and execution discipline.
• Improve and deliver reliable software through continuous integration, automated testing, and code reviews.
• Develop and oversee software engineers within a dynamic, fast-paced, and inclusive setting.
• Lead technical reviews and drive software engineering best practices across the team and larger organization.
• Help define, build, and embody GM engineering culture and principles.

Benefits

• Incentive pay program with payouts based on company performance, job level, and individual performance.
• Potential eligibility for relocation benefits.
• Potential eligibility for GM’s company vehicle evaluation program, subject to program requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager