Principal Engineer, Autonomy Evaluation

General Motors

. Set the multi-year technical direction for autonomous-driving evaluation .

Posted 11/10/2026full-timeSunnyvale • California • United StatesLead💰 $250,000 - $384,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in autonomous systems evaluation, including statistical analysis, machine learning methods, and driving behavior assessment. Proven ability to mentor engineers and influence technical direction across teams while ensuring rigorous evaluation standards.

Highest-signal resume keywords

10+ Years Experience In Autonomous SystemsStrong Production Python SkillsDeep Experience In Statistical EvaluationsExperience In Autonomous Driving Or Field RoboticsAbility To Influence Without Authority

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EvaluationStatistical AnalysisExperimental DesignHypothesis TestingData VisualizationSQL SkillsVLM ApplicationML Model InterpretabilityProblem DefinitionDriving Behavior Analysis

Soft Skills

Stakeholder EngagementMentorshipClear CommunicationInfluencing PeersProblem Resolution

Tools & Technologies

PythonSQLC++Simulation ToolsAutonomy Stack Code

Certifications & Qualifications

Bachelor's Degree In Computer ScienceMaster's Degree In RoboticsPhD In Machine LearningMotor Vehicle Report Review Completion

Industry Keywords

Autonomous DrivingRoboticsData ScienceDriving Logs AnalysisAV Sensor Data

Tech Stack

Tools & technologies

PythonSQLC++

About the role

Key responsibilities & impact

Set the multi-year technical direction for autonomous-driving evaluation
Develop methods to evaluate overall driving behavior, including learned or VLM-based judges, expert-human comparisons, counterfactual and closed-loop analysis, and unknown failure-mode discovery
Define evaluation methods and metrics for perception, prediction, planning, localization, and other learned components
Trace poor driving to the responsible subsystem or interaction and measure how errors affect driving outcomes
Define methods for measuring software or model improvements, regression detection, and version-to-version comparisons
Convert observed behavior into ranked problems using metrics, scene classifiers, and Pareto analysis
Drive problem resolution with the teams responsible for fixes
Ensure scientific rigor through sampling, statistical confidence, metric validity, and simulation-to-road agreement
Make evaluation assumptions and limitations explicit and resolve disagreements between evaluation signals
Provide clear recommendations to engineering and leadership about changes, confidence, and next steps
Prototype and ship code
Mentor Staff and Senior engineers through research and design reviews and written technical direction
Partner with Autonomy, Simulation, Systems, Safety, and Software Validation teams
Inform software release decisions with evaluation evidence

Requirements

What you’ll need

10+ years of experience in autonomous systems, robotics, ML evaluation, or applied data science
Track record of turning analysis into decisions and shipped improvements
Track record of creating new evaluation or measurement methods adopted beyond the candidate's own team
Deep experience designing statistically sound evaluations of dynamic systems, including sampling, confidence intervals, experimental design, hypothesis testing, and precision and recall of classifiers on time-series data
Strong production Python and SQL skills, including testing and code review
Record of defining and sizing problems from raw observations and driving them to resolution with trusted data
Ability to influence without authority and align peers, partner teams, and leadership on technical direction
Strong stakeholder engagement with Autonomy, Simulation, Safety, and Software Validation partners
Experience growing senior engineers through mentorship, design reviews, and written technical direction
Ability to turn ambiguous questions and uncertain results into clear recommendations for executive, engineering, and cross-functional audiences
Bachelor's, Master's, or PhD in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, Statistics, Data Science, or a related field, or equivalent practical experience
Experience in autonomous driving or field robotics, including large-scale analysis of driving logs and AV sensor data from simulation and on-road testing
Experience producing evaluation evidence for validation and release decisions, ideally for driver-assistance or automated-driving products
Experience applying VLMs or LLMs to event classification, triage, or scenario discovery
Experience with ML model interpretability, such as attribution, ablations, or embedding analysis
Strong data-visualization skills
Familiarity with C++, especially for reading or contributing to autonomy stack code
Successful completion of a motor vehicle report review for eligibility for the company vehicle evaluation program
Applicants may be required to complete role-related assessments and/or pre-employment screening

Benefits

Comp & perks

Medical, dental, and vision benefits
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts
Company vehicle evaluation program, subject to successful motor vehicle report review