Staff Artificial Intelligence Machine Learning Engineer

Overview General Motors is seeking a Staff AI/ML Engineer for the Vehicle Mechatronic Embedded Controls (VMEC) Analytics team. The team delivers production AI/ML solutions for high‑impact diagnostics, prognostics, and test‑effectiveness use cases. This is a hands‑on practitioner role focused on building, shipping, and operating real systems – not on academic research. The Staff AI/ML Engineer will serve as a senior individual contributor within an established AI/ML leadership group, providing deep technical expertise, shaping implementation approaches, and mentoring others while collaborating on overall strategy. Responsibilities Design, build, and operate end‑to‑end AI/ML solutions (data pipelines, models, services, and tools) for diagnostics, prognostics, and test analytics. Implement production‑grade ML pipelines on platforms such as Azure and Databricks, covering data ingestion, feature engineering, training, evaluation, and inference for batch and streaming workloads. Develop and maintain robust, observable ML services and internal tools that make complex vehicle and field data easy to use for engineers and technical stakeholders. Apply practical ML and statistical methods (e.g., tree‑based models, time‑series and anomaly detection, deep learning where appropriate) with a focus on reliability, explainability, and impact. Own model and data observability in production, including metrics, dashboards, alerts, and remediation workflows for drift, data quality, and performance regressions. Partner with data engineering to define and use industrialized and vectorized data products that support search, RAG, and analytics at scale. Review designs and code, mentor AI/ML practitioners, and help set high standards for testing, logging, deployment, and documentation. Collaborate with diagnostics/prognostics SMEs, validation, safety, and program teams to prioritize work, define success metrics, and embed solutions in day‑to‑day engineering workflows. Required Qualifications Graduate degree (Master’s or PhD) in Computer Science, Data Science, Machine Learning, Statistics, Engineering, or a closely related quantitative field. 7+ years of hands‑on experience designing, building, and operating machine learning systems in production environments. Strong proficiency in Python (production‑quality code, testing, packaging) and SQL, with experience working in shared, multi‑developer codebases. Practical experience with core ML frameworks such as PyTorch, TensorFlow, or scikit‑learn, and with MLOps tooling (e.g., MLflow, CI/CD, model registries, experiment tracking). Experience building data and ML workloads on cloud platforms, preferably Microsoft Azure, and working with Databricks, Spark, or similar distributed processing frameworks. Demonstrated ability to turn ambiguous real‑world problems into shippable AI/ML solutions, owning the details from data exploration through deployed service and ongoing operation. Strong understanding of ML system behavior in production (data issues, non‑stationarity, latency, throughput, failure modes) and comfort debugging with logs, metrics, and traces. Excellent communication and collaboration skills, with a track record of influencing decisions and mentoring other AI/ML practitioners. Preferred Qualifications 10+ years of applied machine learning or data science experience, including ownership of high‑impact, production AI systems. Experience with vehicle, fleet, or telematics data, or adjacent domains with rich time‑series and reliability data. Background in diagnostics/prognostics modeling (e.g., fault classification, anomaly detection, degradation modeling, survival analysis). Experience building vector search and retrieval‑augmented generation (RAG) or similar production AI applications that integrate foundation models with structured data. Familiarity with Azure Cognitive Services or similar managed AI services and how to combine them pragmatically with custom ML for robust production solutions. Demonstrated impact in raising engineering standards and building AI/ML engineering capability across teams. Prior experience in automotive, embedded controls, or software‑defined vehicle programs, or other safety‑critical domains. Sponsorship & Relocation GM does not provide immigration‑related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc). This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week or other frequency dictated by the manager. This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at View phone number on click.appcast.io. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying. EEO Statement General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. 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