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Data Science Engineering Leader
beBeeMlOp
Job Title
MLOps Engineering Manager
Key Responsibilities
- Lead, mentor, and manage a team of engineers responsible for AI solution development and MLOps / LLMOps infrastructure.
- Drive the successful delivery of applied AI projects, including LLM-enabled applications, clinical decision support tools, and patient cohort analytics.
- Own and evolve the team's engineering practices, including source control workflows, CI/CD pipelines, IaC, observability, testing, and release processes.
- Support responsible AI development by contributing to risk assessments and governance reviews.
- Collaborate closely with IT, research, clinical, and vendor partners to translate needs into buildable technical plans.
Requirements
- Healthcare data environments, including Epic Cogito, FHIR, and OMOP.
- Workflow orchestration tools (e.g., Azure Data Factory, Apache Airflow).
- LLMOps and MLOps platforms (e.g., MLflow, PromptFlow).
- Generative AI and NLP tools (e.g., Azure OpenAI, Azure AI Foundry, John Snow Labs).