Software Systems Engineer, Release Reliability & Automation (Autonomous Vehicles)

Job Overview You will be part of a core team that ensures safe, reliable, and scalable releases of the Autonomous Vehicle (AV) software stack through automation, data‑driven reliability insights, and systematic validation processes. The mission is to accelerate the velocity and stability of AV releases by unifying software engineering, reliability analysis, and release automation under one cohesive framework. Key Responsibilities Design and implement automated release pipelines that integrate simulation, on‑road, and CI/CD validation signals to assess software readiness. Establish release reliability metrics and dashboards to quantify build quality, regression trends, and confidence of software deployment. Collaborate with AI/ML, Simulation, and Systems Engineering teams to ensure robust and reproducible evaluation of release candidates. Develop automated triage and failure analysis systems to identify and categorize root causes of reliability or stability regressions. Integrate data pipelines for continuous monitoring of release health, including automated collection of test, simulation, and telemetry data. Drive systematic improvements in release readiness criteria, defining measurable gates and pass/fail logic tied to product safety and reliability standards. Develop frameworks for continuous release validation, ensuring each ML or software iteration is tracked, reproducible, and explainable. Communicate insights and reliability findings to developers, QA, and leadership to influence roadmap prioritization and technical debt mitigation. Map reliability and automation processes to the broader safety case framework, ensuring compliance with relevant standards and internal governance. Required Qualifications Strong proficiency in Python and SQL. Proven experience in CI/CD systems (e.g., GitHub Actions, Jenkins, GitLab, or equivalent). Prior experience implementing ELT/ETL pipelines for quality monitoring, reliability, or release metrics. Solid understanding of system reliability concepts, including regression tracking, flakiness detection, and automated triage. Strong analytical, debugging, and problem‑solving skills across large‑scale software systems. Experience integrating simulation or hardware‑in‑loop testing into automated pipelines. Track record of cross‑functional collaboration across engineering, QA, and operations teams. Ability to learn quickly and operate effectively in a dynamic, high‑stakes environment. Excellent communication skills for presenting data‑driven insights to engineering and leadership stakeholders. Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent experience. Bonus Points Experience with release governance frameworks for ML or AV systems. Familiarity with reliability engineering methodologies (MTBF, FMEA, reliability growth analysis). Knowledge of AV/ADAS software architectures and simulation validation loops. Experience building metrics pipelines in cloud environments (AWS, GCP, or Azure). Familiarity with data visualization and observability tools (Grafana, Superset, Power BI, etc.). Experience using Jira, GitHub Projects, or equivalent tools for release tracking and reliability triage. Benefits From day one, we support your well‑being at work and at home so you can focus on realizing your ambitions. Detailed information is available in our Total Rewards resources. Equal Employment Opportunity General Motors is committed to a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. All employment decisions are made on a non‑discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. #J-18808-Ljbffr General Motors