Head of Data & AI Platform — Enterprise-Scale ML

Medline Industries, LP

Northbrook (IL)

On-site

USD 203,000 - 305,000

Full time

8 days ago

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Benefits offered by this job

Health insurance
401(k) contributions
Paid time off

Job summary

Medline Industries, LP seeks a Head of Data & AI Platforms to lead the engineering organization building and operating the foundation that enables AI to transform healthcare at scale.

You will own the enterprise Data and AI platforms, evolving them into a unified, production-grade Data + AI platform that supports ML, GenAI, and emerging enterprise AI workloads while ensuring reliability, security, and cost efficiency.

Qualifications

  • 15+ years of engineering leadership experience in data platforms, distributed systems, or AI/ML infrastructure.
  • Deep hands‑on knowledge of modern cloud data platforms and production AI systems.
  • Ability to lead engineering teams and deliver scalable, reliable platforms.

Responsibilities

  • Own the enterprise Data and AI Platforms roadmap, architecture, and engineering best practices.
  • Evolve the data platform into a unified Data + AI platform supporting ML/GenAI workloads.
  • Lead Data Engineering, MLOps, and AI Platform teams as a high-performing org.
  • Define production readiness, SLAs, and cost-efficient platform governance.
  • Drive adoption through developer tools, self-service, and onboarding paths.

Skills

Cloud data platforms
MLOps
Distributed systems
Leadership
Platform as a product

Education

Bachelor's degree in CS/Engineering
Master's degree (preferred)

Tools

Databricks
Azure Data Factory
Azure Data Lake
Azure Synapse
Microsoft Fabric
Power BI

Job description

Medline Industries, LP seeks a Head of Data & AI Platforms to lead the engineering organization building and operating the foundation that enables AI to transform healthcare at scale.

You will own the enterprise Data and AI platforms, evolving them into a unified, production-grade Data + AI platform that supports ML, GenAI, and emerging enterprise AI workloads while ensuring reliability, security, and cost efficiency.

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