As a member of the core AV software reliability team , you will be responsible for ensuring safe, stable, and scalable Autonomous Vehicle (AV) software releases by turning failures into actionable engineering insights at scale.
This is a software-first, platform-focused role. You will work primarily across the AV platform software stack (frameworks, runtime, services, orchestration, data pipelines) and its interaction with vehicle hardware and compute —not cloud infrastructure or hardware design.
The mission of this role is to:
You will do this through intelligent triage, deep software debugging, and AI-assisted failure analysis across simulation, CI, HIL, SIL, and on-road environments , ensuring that failures are:
You will collaborate closely with AV software engineers, ML engineers, systems engineers, test platform owners, and release/safety stakeholders to ensure reliability signals directly influence engineering priorities and release decisions .
If you are passionate about software reliability, failure analysis, and building AI-driven systems that help organizations learn faster from complex ML-based AV software, this role is for you.
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Own the AV software reliability triage framework for the on-vehicle / AV platform stack, defining how failures from simulation, CI, HIL/SIL, and on-road validation are detected, grouped, and escalated into actionable tickets and insights.
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Vehicle compute and hardware interfaces (sensors, ECUs, networks)
Connecting failure symptoms (logs, time-series, traces) to clear solution paths and corrective actions.
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Ingest logs, metrics, traces, and test results across CI, simulation, and vehicle runs
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Strong proficiency in Python for automation, log analysis, data processing, and reliability tooling.
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Proven experience with CI/CD systems (e.g., GitHub Actions, Jenkins, GitLab CI or equivalent) used to run automated tests for complex software systems.
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Hands-on experience implementing ETL/ELT pipelines for reliability, quality, or system health monitoring (e.g., ingesting logs/metrics from test runs, building reliability datasets).
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Track record of effective cross-functional collaboration with software engineering, QA, test platform, and systems teams .
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Bachelor’s, Master’s, or PhD in Computer Science, Electrical/Computer Engineering, Robotics, or a related field — or equivalent software-focused experience .
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Familiarity with reliability methodologies (e.g., FMEA, reliability growth analysis, MTBF trends) applied to software and integrated AV platforms.
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Familiarity with observability and visualization tools (e.g., Grafana, Superset, Power BI, or similar) for reliability dashboards and on-call / triage workflows.
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Experience using Jira, GitHub Projects , or similar tools to design reliability triage workflows, routing, SLAs, and dashboards.
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 $123,200 to $189,100. 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
