Senior Manager AV Evaluation

The Evaluation team builds and evolves the evaluation ecosystem that powers the development and scaling of GMs autonomous driving technology. We develop metricsevaluation infrastructureautomated 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 GMs core evaluation platforms and infrastructure turn system-level results into clear feedback for engineering and leadership and help accelerate validated AV deployment at scale.

We are looking for a Senior Manager to lead a critical autonomy evaluation area spanning platform methodology and organizational execution. This leader will combine deep technical judgment strong people leadership strategic planning and cross-functional influence to define how evaluation supports product safety and release decisions across GMs autonomous driving programs.

WhatYoullDo

• Own the strategy roadmap and operating plan for a distinct Autonomy Evaluation business areaspanningmethodology platforms and infrastructureensuring alignment with autonomy product goals safety priorities and release needs.

• Define and evolve the end-to-end evaluation strategy for autonomy performance including scenario coverage behavioral quality measurement trend detection risk assessment and release-gating readiness.

• Drive cross-functional alignment with Autonomy Simulation Systems and Safety organizations to translate ambiguous validation needs into clear priorities roadmaps and execution plans.

• Oversee evaluation approaches for ML components acrossperception prediction and planning ensuring methods are explainable scalable and useful to development and verification teams.

• Guide the team in developing new statistical and machine learning methods to quantify performance andidentifybehavior patterns across scenes and operational domains.

• Help the organization leverage emerging AI techniques including VLMs and LLMs where appropriate to classify autonomy performance and prioritize validation work with human-in-the-loop review.

• Maintain a high technical bar throughstrong systemdesign code review testing observability and engineering bestpractices.

• Drive the development of scalable evaluation infrastructure including data pipelines workflow orchestration developer tooling and service interfaces that improve reliability and iteration speed.

• Translate system-level resultsand platform health signalsinto clear feedback for engineering and leadership and drive execution against high-priority evaluation outcomes.

Leadership Responsibilities

• Build and lead a high-performing inclusive engineering organization through hiring manager development coaching and feedback.

• Lead through managers and senior technical leaders creating strong accountability healthy operating rhythms and clear ownership across teams.

• Create clarity across priorities roadmaps dependencies and staffing plans for a technically complex cross-functional domain.

• Establish org-level goals KPIs and success measures for evaluation quality scalability insight generation and execution effectiveness.

• Guide investment and resource decisions across near-term delivery and long-term platform capabilities balancing immediate program needs with durable infrastructure andmethodologyimprovements.

• Raise the quality of execution through strong planning discipline design reviews metrics and decision-making mechanisms.

• Resolve complex cross-team conflicts and align stakeholders to drive progress on high-priority issues.

• Collaborate with senior leadership to shape long-term strategy for autonomy evaluation and influence organization-wide decisions that affect AV quality and release confidence.

Your Skills & Abilities (Required Qualifications)

• 8 years of relevant experience in robotics autonomous systems software data analysis ML evaluation autonomy analyticsor large-scale data/infrastructure platformswitha track recordof delivering complex software or data systems.

• 5 years ofpeopleleadership experience in complex engineering organizations including leading managers or senior technical leaders.

• Demonstrated ownership of a distinct technical or business area including strategy roadmap execution planning KPI management and cross-functional outcomes.

• Demonstrated technical leadership including driving architectural decisions influencing cross-team designs and owning complex services or platforms end-to-end.

• Experience building or leading production infrastructure for large-scale data processing workflow orchestration observability and service reliability.

• Experiencedeveloping Python/C in production team environments including testing performance and code review.

• Experience evaluating dynamic systems using numerical statistical and/or machine learning methods including time-series data state derivatives dynamics and interconnected subsystems.

• Strong analytical curiosity and a disciplined approach to root-causing anomalous data and system discrepancies.

• Strong ability to translate ambiguous evaluation needs and complex technical findings into clear plans decisions and communication for executive engineering and cross-functional audiences.

• Bachelors Masters or PhD in Computer Science Robotics Mechanical or Aerospace Engineering Machine Learning Data Science or a related field or equivalent practical experience.

What Will Give You a Competitive Edge (Preferred Qualifications)

• Experience in autonomous driving or field robotics including interpreting results from simulation and field experiments.

• 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 experiment databases platform services or evaluation infrastructure.

• 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.

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 New York Colorado California or Washington.

• The salary range for this role: $296300 - $453900. 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.

• 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.

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.

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