Senior ML Engineer, AI Platforms & MLOps

McKesson; Cork; A distancia; EUR 72.000 - 120.000; Jornada completa

Descripción de la vacante

McKesson seeks a Sr. Specialist, Machine Learning Engineering to design, build and scale production-grade AI/ML and LLM solutions. You will lead scalable ML platforms, pipelines and deployment frameworks, partnering with cross-functional teams to deliver measurable business impact.

You will provide technical leadership across the AI lifecycle, from experimentation to deployment, observability, governance and continuous improvement, while mentoring engineers and driving best practices.

Formación

• 7+ years designing, building and supporting ML in enterprise environments.
• Bachelor’s degree or equivalent in CS/Engineering/DS/IS.
• Strong Python software engineering and modern development practices.
• Experience deploying ML models into production cloud environments.
• Hands-on MLOps: CI/CD, model lifecycle, automation and monitoring.
• Experience with Azure ML, Azure Databricks or similar cloud ML platforms.
• Docker and production deployment patterns.

Responsabilidades

• Lead design, development, deployment and operation of enterprise-scale AI/ML solutions.
• Build and productionize ML pipelines using Azure ML, Databricks and cloud-native services.
• Establish MLOps and LLMOps practices including CI/CD, versioning and monitoring.
• Develop scalable deployment architectures with containers and IaC.
• Mentor engineers and collaborate with data scientists to move prototypes to production.

Conocimientos

Python programming

ML/AI engineering

Cloud computing

MLOps

Stakeholder communication

Educación

Bachelor's degree in CS/Engineering/Data Science/Info Systems

Herramientas

Azure Machine Learning

Azure Databricks

Docker

Kubernetes

Terraform

Descripción del empleo

McKesson seeks a Sr. Specialist, Machine Learning Engineering to design, build and scale production-grade AI/ML and LLM solutions. You will lead scalable ML platforms, pipelines and deployment frameworks, partnering with cross-functional teams to deliver measurable business impact.

You will provide technical leadership across the AI lifecycle, from experimentation to deployment, observability, governance and continuous improvement, while mentoring engineers and driving best practices.