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Machine Learning Operations Engineer II
GM Financial. Design, build, and operate cloud-based MLOps capabilities that support the full lifecycle of analytical and generative AI models .
Tech Stack
Tools & technologiesAzureCloudDockerKubernetesPythonSparkSQL
About the role
Key responsibilities & impact- Design, build, and operate cloud-based MLOps capabilities that support the full lifecycle of analytical and generative AI models
- Blend machine learning engineering, data engineering, and software engineering with a focus on automation, scalability, governance, and production readiness
- Work with technologies such as MLflow, Databricks, Azure Machine Learning, CI/CD pipelines, containerization, and event-driven architectures
- Partner closely with data science, IT, and business teams to deliver secure, compliant, and high-impact AI solutions
Requirements
What you’ll need- 2-4 years as Data Scientist or machine learning engineer or similar quantitative field required
- High School Diploma or equivalent required
- Master’s Degree in the field of Computer Science/Engineering, Analytics, Mathematics, or related discipline preferred, PhD preferred
- Proven hands-on experience across the full ML/MLOps lifecycle, including MLflow and platforms such as Databricks, Azure ML, or SageMaker
- Experience operationalizing GenAI solutions, including LLM patterns (e.g., RAG), prompt/version management, evaluation, safety, and monitoring
- Strong software and cloud engineering fundamentals, including CI/CD, containerization (Docker), and Kubernetes (AKS)
- Experience with event-driven and streaming architectures and modern cloud-native design patterns
- Advanced skills with Python, SQL, and large-scale data platforms (e.g., Spark, Delta, lakehouse architectures)
- Ability to clearly communicate technical trade-offs and connect AI delivery to business and financial outcomes.
Benefits
Comp & perks- Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learning engineeringdata engineeringsoftware engineeringMLOpsPythonSQLCI/CDcontainerizationKuberneteslarge-scale data platforms
Soft Skills
communicationcollaborationproblem-solvingtechnical trade-offs
Certifications
Master’s DegreePhD