Reliability Engineer (Autonomous Vehicles)

Job Description

The Role

You will be part of a core reliability team responsible for ensuring safe, stable, and scalable Autonomous Vehicle (AV) software releases by turning failures into actionable insight at scale. The mission of this role is to improve learning velocity from failures , reduce reliability escapes, and increase confidence in production readiness through intelligent triage, deep debugging, and data-driven analysis.

This role is reliability-first . Release automation, CI/CD, and validation infrastructure are tools-not the goal. You will work across simulation, CI, and on-road environments to ensure failures are correctly understood, consistently categorized, and rapidly connected to the right solution space.

You will collaborate closely with AI/ML engineers, Systems Engineering, Test Platform owners, Release Engineers, and Safety stakeholders to ensure reliability signals meaningfully influence engineering priorities and release decisions.

If you are passionate about reliability engineering, failure analysis, and building systems that help organizations learn faster from complex ML-driven software, we want to talk to you.

What You'll Be Doing

• Own the reliability triage framework for the AV software stack, defining how failures from simulation, CI, and on-road validation are detected, categorized, and escalated into actionable insights.

• Perform deep debugging and root-cause analysis across autonomy software, ML pipelines, and system integrations, connecting failure symptoms to clear solution paths and corrective actions.

• Design and evolve automated triage mechanisms and reliability taxonomies , improving regression detection, flakiness identification, and signal quality as the system and models evolve.

• Build and govern reliability data pipelines , providing continuous visibility into stability trends, recurrence patterns, and systemic risks that impact release readiness.

• Translate reliability findings into decision-grade communication , influencing prioritization, technical debt reduction, and release confidence in partnership with engineering, safety, and systems stakeholders.

What You Must Have

Strong proficiency in Python and SQL for automation, analysis, and data pipelines

Proven experience with CI/CD systems (GitHub Actions, Jenkins, GitLab, or equivalent)

Hands-on experience implementing ETL/ELT pipelines for reliability, quality, or system health monitoring

Solid understanding of reliability engineering concepts , including regression tracking, flakiness detection, and failure classification

Strong analytical and cross-stack debugging skills in large-scale software systems

Experience integrating simulation, HIL, or system-level test signals into automated analysis workflows

Track record of effective cross-functional collaboration across engineering, QA, and platform teams

Ability to operate autonomously in high-ambiguity, safety-critical environments

• Excellent communication skills for presenting data-driven reliability insights to engineering and technical leadership

Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field-or equivalent experience.

Bonus Points

Experience with reliability governance in ML-based or AV systems

Familiarity with reliability methodologies (FMEA, reliability growth analysis, MTBF trends)

Knowledge of AV / ADAS software architectures and simulation-to-road validation loops

Experience building reliability or analytics pipelines in cloud environments (AWS, GCP, Azure)

Familiarity with observability and visualization tools (Grafana, Superset, Power BI, etc.)

• Experience using Jira, GitHub Projects , or similar tools for reliability tracking and triage workflows

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

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