설명
The Role
You will be part of a core team that enables safe, reliable, and scalable releases of the Autonomous Vehicle (AV) software stack through intelligent automation, AI-enabled engineering workflows, and data-driven validation. The mission is to accelerate AV software development and release velocity by reducing manual effort, improving test and release visibility, and applying AI to engineering processes.
In this position, you will collaborate closely with Release Engineers, Systems Engineers, DevOps, QA, and AI/ML teams to design and implement automated release validation pipelines, integrate simulation and hardware-in-loop testing, build engineering metrics, and develop AI-enabled solutions for test analysis, failure classification, defect triage, reporting, and workflow orchestration.
You will help establish practical standards for evaluating, governing, and scaling automation and AI solutions while improving release readiness, software quality, and engineering productivity. If you are passionate about applying intelligent automation and systems thinking to accelerate the development of safe, high-quality ML-driven AV software, we want to talk to you.
What You’ll Be Doing
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Lead the design and implementation of automation across software development, testing, release, and operational workflows.
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Identify opportunities to apply AI, machine learning, and LLM-based tools to improve engineering productivity and decision-making.
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Build AI-enabled solutions for test analysis, failure classification, defect triage, documentation, reporting, and workflow orchestration.
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Develop and maintain scalable CI/CD integrations supporting simulation, hardware-in-loop, regression, and release validation activities.
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Build data pipelines that combine engineering, QA, simulation, test, and release information into actionable insights.
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Establish practical methods for evaluating the accuracy, usefulness, traceability, and adoption of AI-enabled engineering tools.
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Automate repetitive manual processes and measure improvements in cycle time, test efficiency, defect prevention, and engineering throughput.
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Improve visibility into test health, regression trends, flaky tests, failure patterns, and release readiness.
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Collaborate with engineering, QA, operations, data, and program teams to understand pain points and deliver effective automation solutions.
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Integrate tools such as Jira, GitHub, dashboards, observability platforms, and cloud services into unified engineering workflows.
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Help define standards and governance for maintainable, secure, observable, and scalable automation and AI solutions.
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Communicate technical findings, process improvements, and measurable business impact to engineering and leadership stakeholders.
What You Must Have
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Strong proficiency in Python and SQL .
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Proven experience in CI/CD systems (e.g., GitHub Actions, Jenkins, GitLab, or equivalent).
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Hands-on experience developing ELT/ETL pipelines and integrating data from engineering, QA, simulation, and operational systems.
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Experience applying AI, machine learning, or LLM-based solutions to improve engineering productivity, test analysis, defect triage, documentation, or decision-making.
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Ability to evaluate AI-generated outputs for accuracy, consistency, traceability, and usefulness in engineering workflows.
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Strong analytical, debugging, and problem-solving skills across large-scale software systems.
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Experience integrating simulation or hardware-in-loop testing into automated pipelines.
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Track record of cross-functional collaboration across engineering, QA, and operations teams.
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Ability to learn quickly and operate effectively in a dynamic, high-stakes environment.
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Excellent communication skills for presenting data-driven insights to engineering and leadership stakeholders.
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Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent experience.
Bonus Points!
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Experience developing AI agents, copilots, retrieval-augmented generation systems, workflow automation, or intelligent engineering tools.
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Experience establishing governance, evaluation, monitoring, and security practices for AI-enabled engineering solutions.
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Knowledge of AV/ADAS software architectures, simulation validation loops, or automated vehicle testing.
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Experience with release governance, quality gates, or compliance processes for ML, AV, or safety-critical systems.
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Familiarity with reliability engineering concepts such as MTBF, FMEA, reliability growth analysis, and failure trend analysis.
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Experience building automation and metrics pipelines in AWS, GCP, Azure, or equivalent cloud environments.
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Familiarity with data visualization and observability tools such as Grafana, Superset, Power BI, or equivalent.
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Experience integrating Jira, GitHub Projects, or similar tools into automated release tracking, workflow orchestration, or engineering triage.
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Experience measuring automation impact through cycle-time reduction, defect prevention, reduced manual effort, improved test efficiency, or increased engineering throughput.
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
다양성 정보
General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다. 자세한 정보는 GM 채용 과정 안내를 참고하십시오.
공평한 취업 기회 선언 (미국)
General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다. 자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다.
숙소 (미국 및 캐나다)
General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.
