Machine Learning Engineer- AI Data Platform (Minneapolis, MN)

Machine Learning Engineer- AI Data Platform (Minneapolis, MN) MOBE guides people to better health and more happiness by helping them discover connections between lifestyle aspects that affect health and well‑being. Our innovative solutions rely on robust data analytics, digital applications, and a philosophy of compassion. We value a collaborative culture and a workforce that embraces differences and grows together. Role Overview As an AI Engineer, you will be a core builder of the AI Data Platform, designing and operating the infrastructure that powers AI‑driven insights across the organization. You will build intelligent data pipelines, production‑grade ML systems, and AI‑enabled features that translate complex data into actionable outcomes. Applicants must be authorized to work in the U.S. This position does not sponsor work visa. Responsibilities Build AI‑first data pipelines: Design, implement, and maintain scalable pipelines that support model training, inference, and analytics use cases. Deploy production ML systems: Develop, deploy, and monitor models using AWS SageMaker, ensuring reliability, observability, and performance. Implement Retrieval‑Augmented Generation (RAG): Architect and maintain RAG‑based systems that combine structured and unstructured data for AI insights. Operationalize ML lifecycle management: Use MLflow for experiment tracking, model versioning, and lifecycle management. Design feature infrastructure: Build and manage feature stores (e.g., Feast, Tecton, SageMaker Feature Store) for reusable features. Orchestrate complex workflows: Create and manage Apache Airflow DAGs for data transformations, model pipelines, and AI workflows. Enable analytics consumption: Partner with BI teams to integrate ML outputs into internal reporting. Translate business questions into AI solutions: Collaborate with stakeholders to convert ambiguous problems into measurable, data‑driven solutions. Uphold data quality & governance: Ensure pipelines and models adhere to data governance, security, and quality standards. Collaborate cross‑functionally: Work with Data Science, Analytics Engineering, Medical Economics, and DataOps to align platform capabilities with business priorities. Qualifications Required: 5‑7 years of experience in ML engineering. Strong proficiency in Python and SQL. Proven experience building and deploying models in production, monitoring performance. Hands‑on experience with AWS SageMaker for training, deployment, and inference. Experience designing or operating RAG systems that integrate LLMs with enterprise data. Experience with MLflow for experiment tracking and model registry. Experience with Apache Airflow for orchestration. Solid foundation in data engineering concepts: modeling, versioning, testing. Ability to partner with Med Econ and BI teams to ensure outputs are interpretable and trusted. Preferred: Experience with AWS Bedrock or Aider for LLM orchestration. Experience with dbt. Familiarity with feature store architectures. Experience integrating ML outputs into BI tools (Tableau, Looker, QuickSight). Experience with CI/CD pipelines and Git‑based workflows. Exposure to healthcare or regulated data environments (plus). Nice to Have: Knowledge of Docker and Kubernetes. Experience with data observability, model drift detection, or AI governance tooling. Experience fine‑tuning large language models for domain‑specific use cases. Benefits Paid time off Medical, dental, and vision insurance Life and disability insurance 401(k) with company match Tuition reimbursement Additional benefits available to eligible employees Salary range: $114,000‑$130,000 based on experience. Employment Classification Full‑time position. EEO Statement We are an equal employment opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability status, veteran status, or any other protected characteristic. Location Minneapolis, MN Status This position is currently accepting applications. #J-18808-Ljbffr