Principal Software Engineer – Autonomy Behavior Validation

General Motors

Principal engineer building counterfactual simulation and behavior-validation systems for General Motors’ autonomous-vehicle safety decisions. Leading scalable scenario reconstruction, human-response modeling, and release evidence.

Posted 9/3/2026full-timeSunnyvale • California • 🇺🇸 United StatesLead💰 $238,700 - $365,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in counterfactual behavior evaluation, human behavior modeling, and simulation evaluation at scale, with a strong focus on safety-critical validation and technical leadership across multidisciplinary teams.

Highest-signal resume keywords

Counterfactual Behavior EvaluationHuman Behavior ModelingSimulation Evaluation at ScaleTechnical LeadershipPython Programming

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Systems EngineeringSimulation DevelopmentVehicle DynamicsData Quality AnalysisParameter ExtractionScenario GenerationCrash ReconstructionIncident AnalysisValidation MethodologiesHuman Factors Engineering

Soft Skills

Strong Written CommunicationStrong Verbal Communication

Tools & Technologies

Simulation SoftwareAnalysis ToolsValidation Software

Industry Keywords

Autonomous VehiclesRoboticsSafety-Critical ValidationHuman FactorsCommercial Fleet Evaluation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Set the technical strategy and architecture for counterfactual behavior evaluation
Operationalize safety-defined attentive-human benchmarks, counterfactual simulation following human intervention, alternate-policy comparisons, and controlled scene perturbations
Convert real incidents and simulation events into executable, provenance-preserving scenarios
Implement and validate human and other road-user response models against benchmarks and requirements
Define and deploy scalable pipelines for parameter extraction, scene reconstruction, counterfactual swaps, fuzzing, simulation execution, outcome estimation, and analysis of large scenario sets
Establish validation methods for the counterfactual product and outputs, including baseline comparisons, replay and closed-course evidence, model limitations, confidence, traceability, and appropriate use of results
Lead work across Behavior, Simulation, Safety, Human Factors, Legal, Product, and Operations
Turn complex results into engineering actions, safety-case evidence, and release recommendations

Requirements

What you’ll need

Master’s degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, human factors, or a related field
10 or more years of professional experience in autonomous vehicles, robotics, vehicle development, simulation, systems engineering, human factors, or safety-critical validation
Proven record of evaluating autonomous vehicles for a commercial fleet, launch, supervised release, or other high-consequence product decision
Strong understanding of human behavior modeling, driver response, perception and reaction time, vehicle dynamics, uncertainty, and the limits of model-based conclusions
Deep experience building or leading counterfactual, replay, crash reconstruction, incident analysis, or comparable simulation-based evaluation capabilities
Professional experience with simulation evaluation at scale, including scenario generation, parameter sweeps, distributed execution, reproducibility, data quality, and trade-offs between fidelity, confidence, runtime, and cost
Strong Python and agentic workflow experience
Comfort designing and reviewing production-quality analysis, simulation, and validation software and using code to investigate engineering questions
Strong written and verbal communication skills, with ability to explain technical results, assumptions, and limitations to engineering and non-engineering stakeholders
Demonstrated technical leadership across organizational boundaries and evidence of setting direction beyond a single project through a methodology, platform, framework, or reusable validation capability adopted by other teams

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company performance, job level, and individual performance
Medical insurance
Dental insurance
Vision insurance
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
Health and wellbeing benefit programs