Senior AI/ML Platform Lead (Databricks)

EY; Milwaukee (WI); À distance; USD 126 000 - 230 000; Plein temps

Résumé du poste

EY is seeking a Manager in Model Engineering within its AI, Data & Engineering team, available across the United States. You will lead production-grade AI/ML pipelines on the Databricks platform, guiding cross-functional teams to deliver scalable data engineering and AI solutions for clients.

This role emphasizes responsible deployment, collaboration with data scientists, engineers, and product stakeholders, and delivering measurable business value.

Qualifications

• Bachelor’s degree required (4-year degree).
• 6-10 years of AI, data science, and/or ML experience.
• 2-4 years of direct technical team management.
• 3-4 years building and deploying production AI/ML on the Databricks platform.
• Databricks Certification (Data Engineer/ML/Generative AI) helpful.
• Strong Python, PySpark, and/or Scala skills.
• Excellent communication and collaboration across hybrid/global teams.
• Experience with MLOps/AgentOps on Databricks.

Responsabilités

• Lead AI workstreams from discovery to production deployment and optimization on Databricks.
• Direct teams building data pipelines and AI solutions (ML, generative AI, agentic AI).
• Collaborate with clients and stakeholders to define outcomes and roadmaps.
• Design, build, and govern ontologies and semantic models for AI solutions.
• Deliver production-grade data and AI pipelines with reliable governance.

Connaissances

Python

PySpark

Scala

Strong communication

Team leadership

Databricks

Product-centric development

Formation

Bachelor’s degree (4-year)

Outils

Databricks platform

Databricks SQL

Unity Catalog

Git

Azure DevOps

Description du poste

EY is seeking a Manager in Model Engineering within its AI, Data & Engineering team, available across the United States. You will lead production-grade AI/ML pipelines on the Databricks platform, guiding cross-functional teams to deliver scalable data engineering and AI solutions for clients.

This role emphasizes responsible deployment, collaboration with data scientists, engineers, and product stakeholders, and delivering measurable business value.