Staff Artificial Intelligence Machine Learning Engineer

What You’ll Do

• 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.
• Your Skills & Abilities (Required Qualifications) : Graduate degree (Master’s or PhD) in Computer Science, Data Science, Machine Learning, Statistics, Engineering
• a closely related quantitative field. 7+ years of hands‑on experience designing, building
• 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.
• What Will Give You A Competitive Edge (Preferred Skills) : 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. 

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).&#xa
• 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 your manager}.&#xa
• This job is not eligible for relocation benefits.
• Any relocation costs would be the responsibility of the selected candidate.&#xa
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