Work Arrangement:
This role is categorized as hybrid. This means the successful candidate is expected to report to Sunnyvale, CA three times per week at minimum or other frequency dictated by the business.
The Role
As Engineering Manager for Planner Evaluation, you will be a senior contributor in the Motion Planning team at GM. We develop metrics, automated workflows, and analysis approaches that enable data-driven decisions across autonomy development and verification. In this role, you will lead a team with deep domain expertise in simulation and on-road evaluation workflows used to advance GMs Super Cruise portfolio. You will define the technical vision and multi-quarter roadmap for Planner Evaluation, drive design quality from architecture through validation, and align multiple teams to ship reliable, scalable evaluation solutions that meet Super Cruise program goals.
What You'll Do
- Own multi-quarter roadmap designs and their realization for autonomy planner evaluation.
- Guide other 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, proactively creating test plans for new features and defining useful metrics for analyzing performance.
- Mentor engineers across teams, raising the bar on technical judgment, design quality, and execution discipline.
- Improve and deliver reliable software through continuous integration, automated testing, and code reviews.
- Develop and oversee top-tier software engineers within a dynamic, fast-paced, and inclusive setting.
- Lead technical reviews and drive software engineering best practices across the team and the larger organization.
- Help define, build, and embody GM engineering culture and principles.
Your Skills & Abilities (Required Qualifications)
- Bachelor's, Master's, or PhD in Computer Science, Robotics, Engineering, Machine Learning, Data Science, or related
- 5+ years of experience in engineering analysis, ML evaluation, or autonomy analytics
- 3+ years of experience evaluating dynamic systems using numerical and/or ML approaches, including time-series data and state derivatives
- 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 an 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
What Can Give You a Competitive Advantage (Preferred Qualifications)
- 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 the 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
Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
- The salary range for this role is ($218,800 - $335,300). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
- Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
This Job may be eligible for relocation benefits.
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Skills Required
- Bachelor's, Master's, or PhD in Computer Science, Robotics, Engineering, Machine Learning, Data Science, or a related field
- 5+ years of experience in engineering analysis, machine learning evaluation, or autonomy analytics
- 3+ years of experience evaluating dynamic systems using numerical or machine learning approaches, including time-series data and state derivatives
- 3+ years of experience building and managing high-performing engineering teams
- Strong proficiency developing Python in production team environments, including testing, performance optimization, and code review
- Ability to read, debug, and instrument C++ codebases and core algorithms
- Hands-on familiarity with data visualization libraries for large-scale analysis and reporting
- Demonstrated technical leadership, including architectural decisions, cross-team design influence, and end-to-end ownership of complex services or platforms
- Strong cross-functional communication and ability to convert ambiguous evaluation needs into technical plans
- Strong analytical and root-cause investigation skills for anomalous data and system discrepancies
- Understanding of vehicle dynamics
- Expertise in planning and controls system design
- Experience evaluating robotics or autonomous vehicle systems using camera, lidar, radar, and large-scale time-series data
- Experience with statistical modeling, experimental design, and hypothesis testing for autonomy or simulation evaluation
- Proficiency in SQL and experience with logging, data schemas, evaluation pipelines, and performance monitoring
- Experience with ROS or similar robotics/IPC frameworks, log pipelines, experiment databases, or evaluation platforms
- Experience with computational geometry, linear algebra, PyTorch, and machine learning techniques applied to perception, prediction, planning, or control
- Experience with release gating, risk assessment, and safety-related decisions for autonomous systems
- Experience using AI-assisted development and analytics tools
- Background in robotics or the autonomous vehicle/ADAS industry
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Healthcare Strength — Health coverage is described as comprehensive, spanning medical, dental, vision, mental-health services, virtual care, and wellness resources. Offerings are often portrayed as a standout element of the package.
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Retirement Support — Retirement programs are presented as robust, with employer contributions and matching highlighted as a significant advantage. This support is frequently cited alongside savings tools and financial-wellbeing programs.
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Leave & Time Off Breadth — Paid vacation, numerous holidays, and multiple leave programs are emphasized as part of a broad time-off offering. These elements are commonly noted as meaningful components of total compensation.
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At General Motors, our purpose is to pioneer the innovations that move and connect people to what matters. We’re driving the world forward, together. We’re building vehicle software alongside its hardware, hands-free driving that will lead to autonomy, and EVs that charge your home for an all-electric future.
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Employees engage in a combination of remote and on-site work.
Roles that are categorized as Hybrid mean that the successful candidate is expected to report onsite to the designated facility at least three times per week or other frequency as dictated by the business.










































