Staff Artificial Intelligence Machine Learning Engineer

Job Description

The Role:

General Motors is seeking aStaff AI/ML Engineerfor theVehicle Mechatronic Embedded Controls (VMEC) Analyticsteam.

The team delivers production AI/ML solutions for highimpact diagnostics prognostics and testeffectiveness use cases. This is ahandson practitioner rolefocused on building shipping andoperatingreal 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 technicalexpertise shaping implementation approaches and mentoring others while collaborating on overall strategy.

WhatYoullDo:

• Design build andoperateendtoend AI/ML solutions(data pipelines models services and tools) for diagnostics prognostics and test analytics.
• Implementproductiongrade ML pipelineson platforms such asAzureandDatabricks covering data ingestion feature engineering training evaluation and inference for batch and streaming workloads.
• Develop andmaintainrobust observable ML services and internal toolsthat make complex vehicle and field data easy to use for engineers and technical stakeholders.
• Applypractical ML and statistical methods(e.g. treebased models timeseries and anomaly detection deep learning whereappropriate)with a focus on reliability explainability and impact.
• Ownmodel and data observabilityin production including metrics dashboards alerts and remediation workflows for drift data quality and performance regressions.
• Partner with data engineering to define and useindustrialized and vectorized data productsthat support search RAG and analytics at scale.
• Review designs and codementor AI/ML practitioners and help sethigh standardsfor 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 daytoday engineering workflows.

Your Skills & Abilities (Required Qualifications):

• Graduate degree (Mastersor PhD)in Computer Science Data Science Machine Learning Statistics Engineering or a closely related quantitative field.
• 7 yearsof handson experience designing building and operating machine learning systems in production environments.
• StrongproficiencyinPython(productionquality code testing packaging) andSQL with experience working in shared multideveloper codebases.
• Practical experience with coreML frameworkssuch asPyTorchTensorFlow orscikitlearn and with MLOps tooling (e.g. MLflow CI/CD model registries experiment tracking).
• Experience building data and ML workloads oncloud platforms preferablyMicrosoft Azure and working withDatabricks Spark or similar distributed processing frameworks.
• Demonstrated ability toturn ambiguous realworld problems into shippable AI/ML solutions owning the details from data exploration through deployed service and ongoing operation.
• Strong understanding ofML system behavior in production(data issues nonstationarity latency throughput failure modes) and comfort debugging with logs metrics and traces.
• Excellentcommunication and collaboration skills witha track recordof influencing decisions and mentoring other AI/ML practitioners.

What Will Give YouACompetitive Edge (Preferred Skills):

• 10 yearsof applied machine learning or data science experience including ownership of highimpactproductionAI systems.
• Experience withvehicle fleet or telematics data or adjacent domains with rich timeseries and reliability data.
• Background indiagnostics/prognostics modeling(e.g. fault classification anomaly detection degradation modeling survival analysis).
• Experience buildingvector search and retrievalaugmented generation (RAG)or similarproductionAI applications that integrate foundation models with structured data.
• Familiarity withAzure Cognitive Servicesor similar managed AI services and how to combine them pragmatically with custom ML for robust production solutions.
• Demonstrated impactinraising engineering standardsand building AI/ML engineering capability across teams.
• Prior experience inautomotive embedded controls or softwaredefined vehicleprograms or other safetycritical domains.

About GM

Our vision is a world with Zero Crashes Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day individually and collectively to drive meaningful change through our words our deeds and our culture. Every day we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one were looking out for your well-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

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.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required where applicable to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more visit How we Hire.

Accommodations

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