Senior Software Systems Engineer - Autonomous Vehicles

generalmotors; Sunnyvale (CA); On-site; USD 153,000 - 234,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Tuition assistance

Job summary

General Motors in Sunnyvale, CA seeks a data-driven AV evaluation engineer to own end-to-end execution, design evaluation methodologies, and communicate insights that establish confidence in the end-to-end ML stack.

You will collaborate with AI/ML engineers, simulation teams, and data partners to build scalable processes for evaluating coverage, metrics, uncertainty, and validation confidence.

Qualifications

• Strong Python programming skills for analysis, evaluation, or testing tools.
• Experience designing or implementing testing, simulation, or evaluation frameworks for complex systems.
• Experience with GitHub, Jira, or equivalent tools.
• Demonstrated end-to-end ownership from problem definition to outcome delivery.
• Track record of analytical and systems-engineering work on complex software/hardware systems or ambiguous AI functions.

Responsibilities

• Define AV evaluation and validation processes from concept through implementation, including test-framework requirements, scenario and test-suite design, coverage, metrics, and evidentiary support.
• Design and implement scalable testing and simulation frameworks for test generation, execution, data collection, result aggregation, and reproducible analysis.
• Provide hands-on implementation of infrastructure and data solutions to assess confidence in AV performance using simulation and on-road data.
• Develop and apply methods to evaluate simulation validity, sim-to-real correlation, and predictive value of simulation results.
• Identify metrics, sampling approaches, and analytical methods to improve evaluation workflows.

Skills

Python

Testing frameworks

Data analysis

GitHub/Jira

End-to-end ownership

Analytical thinking

Cross-functional communication

Education

Bachelor’s, Master’s, or PhD in engineering/physics/math/data science

Tools

GitHub

Jira

Job description

Job Description

The Role

You will be part of a team that drives systematic and data-driven improvements to autonomous vehicle software by designing, implementing, and maintaining robust processes for evaluation and validation. We are looking for a highly motivated individual with excellent analytical skills to own end-to-end execution, improve evaluation methodologies, and communicate insights that establish confidence in the quality of our end-to-end ML stack.

In this position, you will work closely with AI/ML engineers, simulation engineers, systems engineers, and data partners to identify, analyze, monitor, and prioritize the signals used to assess performance. You will leverage simulation and on-road data to build scalable processes for evaluating coverage, metrics, uncertainty, and validation confidence.

What you’ll be doing

• Define AV evaluation and validation processes from initial concept through implementation, including test-framework requirements, scenario and test-suite design, coverage, metrics, and the evidence needed to assess confidence in system performance.

• Design and implement scalable testing and simulation frameworks for test generation, execution, data collection, result aggregation, and reproducible analysis.

• Provide hands‑on implementation of infrastructure and data solutions to assess confidence in AV performance using simulation and on‑road data.

• Develop and apply methods to evaluate simulation validity, sim-to-real correlation, and the predictive value of simulation results.

• Proactively scope and identify metrics, sampling approaches, and analytical methods needed to improve evaluation workflows and close gaps in evidence.

• Contribute to automated triage and root‑cause analysis strategies for AV deficiencies, regressions, and uncertainty in an end‑to‑end stack.

• Articulate insights, summaries, limitations, and recommendations to engineers, technical leaders, and other stakeholders based on continuous analysis of AV performance.

• Define and maintain scalable processes to identify, monitor, and improve evaluation KPIs and confidence measures.

• Help connect continuous‑improvement activities to the evidence needed to support safety, systems, and downstream readiness decisions.

What you must have

• Strong Python programming skills, with experience building clear, maintainable analysis, evaluation, or testing tools.

• Experience designing or implementing testing, simulation, or evaluation frameworks for complex software/hardware or cyber‑physical systems.

• Experience with GitHub, Jira, or equivalent tools.

• Demonstrated end‑to‑end ownership, from defining a problem through delivering and communicating the desired outcome.

• A track record of analytical and systems‑engineering work involving complex software/hardware systems or ambiguous AI functions.

• Experience performing root‑cause analysis and applying analytical methods to system or behavioral performance data.

• Ability to creatively solve problems with limited supervision, learn quickly, and operate effectively in a fast‑paced environment.

• Strong cross‑functional communication skills, including the ability to communicate data‑driven findings to leadership.

• Bachelor’s, master’s, or doctoral degree in engineering, physics, applied mathematics, statistics, data science, or a related discipline, or an equivalent combination of education and experience.

Bonus points!

• Experience with autonomous vehicles, ADAS, robotics, or production‑grade robotic systems.

• Hands‑on experience with simulation environments, scenario generation, large‑scale test execution, or analysis of simulation results.

• Experience with statistical methods for product evaluation, risk assessment, sampling, or confidence analysis.

• Experience developing data‑driven metrics, scorecards, coverage measures, or regression‑detection methods.

• Experience with verification and validation, simulation‑to‑real‑world correlation, test automation, or large‑scale evaluation systems.

• Passion for understanding complex robotics and AI systems and turning their behavior into measurable evidence.

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 $153,200 to $234,100. 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

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

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