Johns Hopkins Medicine-posted about 2 months ago
$54 - $94/Yr
Full-time • Manager
Hybrid • Baltimore, MD
5,001-10,000 employees
Hospitals

Johns Hopkins Medicine is building a new generation of AI and data-powered tools that accelerate discovery, improve clinical decision-making, and reduce operational burden across the health system. As a Manager within the Platforms & Integrations team, you will lead engineering efforts at the intersection of applied AI and modern cloud data platforms-powering precision care, accelerating discovery, and enabling scalable software solutions for one of the world's premier health systems. This is a high-impact role for a technically sophisticated leader who thrives in a collaborative, mission-driven environment. General Position Summary: The MLOps Engineering Manager is a hands-on technical leader responsible for growing a team of engineers and data scientists delivering scalable, production-grade systems for the dual goals of clinical research data enablement and AI applications. You will guide the development of clinical decision support tools, multimodal de-identified data assets, and model evaluation toolkits. The ideal candidate combines deep technical skill with a focus on execution-able to design, build, and coach in equal measure.

  • 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.
  • Support team growth and cohesion, enabling a culture of collaboration within and outside your immediate team.
  • Work requires a professional level of knowledge in Information Systems as acquired through completion of a Bachelor's Degree in Information Systems, Business Management, or related field.
  • Work requires demonstrated a minimum of 7 years of experience with computer systems and applications
  • A minimum of 5 years of planning and managing projects.
  • 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)
  • Data science methodologies, including supervised/unsupervised learning, model evaluation, and statistical inference
  • Feature engineering and data productization, including feature stores or reusable data assets
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