설명
The Role
As a Principal Autonomy Behavior Systems Engineer, you will be the technical authority for how GM's autonomous vehicle behavior is defined, evaluated, and judged ready for release. Your scope covers the full range of driving behaviors, from routine maneuvers to rare, safety-critical events. It also covers the whole validation lifecycle, from product requirements through launch and continuous monitoring in the fleet.
You will bring broad, deep expertise in autonomous driving. You know how the autonomy stack produces behavior, where it fails, and what evidence a behavior needs before it is ready for a self-driving fleet. You will work across Behavior, Software, Simulation, Safety, Legal, Product, and Operations to build a validation system that supports sound safety and launch decisions and earns the trust of the engineers and leaders who depend on it.
What You'll Do
- Set the long-term technical strategy and systems engineering approach for autonomy behavior validation across capabilities, programs, and releases. This includes behavior decomposition, metrics, acceptance criteria, coverage, confidence, and traceability.
- Define what "ready" means for autonomous behavior. Connect safety claims, hazard analysis, and requirements to the evidence behind supervised release, driverless launch, and continuous release decisions, and present those recommendations to senior leadership.
- Act as the organization's go-to expert on autonomous driving behavior. Diagnose complex issues across perception, prediction, planning, and controls, and lead the work to close behavioral escapes and coverage gaps using fleet and incident data.
- Design validation strategies that combines simulation, road data, closed-course testing, human references, and expert review. Make deliberate trade-offs among coverage, confidence, fidelity, runtime, and cost.
- Guide validation tools, data pipelines, scorecards, and AI-assisted or agentic workflows toward repeatable, scalable products used by many teams.
- Lead cross-functional technical reviews, mentor engineers, and raise the bar for systems engineering and validation across the AV organization.
Required Qualifications
- Master's degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, or a related field, and 10 or more years of professional experience in autonomous vehicles, robotics, simulation, systems engineering, or safety-critical validation.
- A proven record of evaluating autonomous vehicles for a self-driving fleet, launch, supervised release, or other high-consequence product decision, including owning or materially shaping the go/no-go recommendation.
- Deep, end-to-end expertise in autonomous driving: how each part of the stack (perception, prediction, planning, and controls) shows up as on-road behavior across a wide range of scenarios, road users, and operating conditions.
- Deep systems engineering fundamentals, including decomposition, ODD definition, requirements strategy, V&V planning, and traceability, plus experience leading simulation evaluation at scale.
- Strong Python and agentic workflow experience. You are comfortable designing and reviewing production-quality analysis and validation software and using code to investigate an engineering question quickly.
- Demonstrated technical leadership across organizational boundaries, including setting direction adopted beyond a single team and explaining results, assumptions, and limitations clearly to engineers and senior leaders.
What Will Give You a Competitive Edge
- Experience as a technical lead for validating a driverless commercial launch or an expansion into new operating domains.
- Experience evaluating learned or end-to-end driving systems, including how to characterize their behavior, regressions, and generalization.
- Experience with human benchmarking (such as attentive-human benchmarks) and counterfactual or replay methods, and how they fit within a broader validation strategy.
- Experience building or using a safety case, and familiarity with hazard analysis methods (STPA, FMEA, fault trees) and standards such as ISO 21448 (SOTIF), UL 4600, or ISO 26262.
- Experience with risk quantification and risk acceptance, and with turning legal or regulatory expectations into a defensible compliance strategy.
- Experience designing validation lifecycles, scorecards, confidence rubrics, or behavior protocols used by many engineering teams.
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: is $238,700 to $365,700. 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
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