Tech Lead Manager - Validation Metrics

Job Description

About the Role

As a Tech Lead Manager, Validation Metrics on the Software Validation team within the Autonomous Vehicle (AV) organization, you will own the end-to-end lifecycle of validation metrics for the Super Cruise program?from requirements definition and metric design through implementation, deployment, and continuous monitoring . You will lead a team of systems engineers to design robust, scalable metrics that underpin all of autonomy validation.

Your work will directly support our goals to deliver high-confidence validation signals in simulation and on-road, enable release decisions, and continuously monitor production performance across the SC3 stack.

About the Organization

The Autonomous Vehicle (AV) organization is dedicated to advancing the development of autonomous vehicles through cutting-edge simulation technologies and novel iterative development processes.

The Software Validation team focuses on unlocking software launches and continuous release decisions via simulation-led verification and validation strategies, prototypes, and protocols. Our collaborative environment fosters innovation and excellence, allowing us to push the boundaries of what is possible in autonomous vehicle testing.

What You'll Do

Own Validation Metrics Strategy and Roadmap , ensuring alignment with all stakeholders while delivering metrics commitments on program milestones.

Lead the End-to-End Metric Lifecycle from stakeholder requirements and design through implementation, validation, and continuous monitoring across simulation and road environments.

Accelerate Metric Deployment by identifying and acting on opportunities for automation, agentic offloading, and scale.

Lead a High-Impact Engineering Team of systems engineers, setting technical direction; establishing engineering best practices, and hiring against the metrics and confidence roadmap.

Drive Cross-Functional Collaboration to ensure metrics, slicers, and monitoring signals are usable, trusted, and integrated into scorecards, reports, and decision processes.

Ensure High-Quality Monitoring and Feedback Loops with clear targets on completeness and quality, driving continuous improvement in autonomy performance and safety.

Your Skills & Abilities

• 10+ years of experience in software engineering, data/ML engineering, or robotics , including substantial work on evaluation, analytics, or metrics for complex systems.
• 3+ years of experience managing engineering teams , including hiring, performance management, and technical leadership.
• Strong background in metrics design and evaluation for complex or safety-critical systems (e.g., AV/ADAS, robotics, large-scale ML systems, or similar).
• Proficiencyin Python and SQL for large-scale data analysis and building production-quality analytics or evaluation pipelines; familiarity with C++ or similar languages is a plus.
• Demonstrated ability to translate ambiguous validation and safety goals into concrete metrics , acceptance criteria, and implementation plans.
• Excellent communication and stakeholder management skills , capable of switching between high-level strategy and detailed technical discussions with engineers, data scientists, and non-technical partners.

What Will Give You a Competitive Edge

• Experience with autonomous driving, ADAS, robotics, or other safety-critical domains , especially in validation, safety, or systems engineering roles.
• Solid understanding of the ML lifecycle (data, training, evaluation, deployment), including common pitfalls such as data leakage, covariate shift, and label noise , and how they influence metric design and interpretation.
• Experience with simulation-led validation , including scenario-based testing, golden-set creation, and sim?road correlation metrics.
• Hands-on experience with agentic workflows (LLM-based agents, workflow orchestration frameworks, or similar) used to accelerate analyses, automate documentation, or orchestrate complex data and metric pipelines.
• Background in learned metrics , representation learning , or advanced analytics for evaluation of ML systems, particularly in high-dimensional sensor or trajectory data.
• Track recordof building and scaling new teams or charters , especially in rapidly evolving technical problem spaces like AV validation, ML evaluation, or safety analytics.

+ Compensation:

• The expected base compensation for this role is: $189,300- $290,700. Actual base compensation within the identified 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.

+ Benefits:

• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}.

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

About GM

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Why Join Us

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