AI/ML Data Science Engineering Director – Hybrid Leader

AI Solutions; Chicago (IL); Hybrid; USD 162,000 - 300,000; Full time

Job summary

HCSC is seeking a Senior Director for Data Science Engineering to lead ML engineering efforts that operationalize AI/ML at scale. You will guide a team, collaborate with data scientists, product managers, and IT to deploy dependable solutions.

The role emphasizes MLOps, CI/CD, model deployment, and cloud infrastructure, with a hybrid work model requiring 3 days in-office and a focus on healthcare outcomes for members.

Qualifications

• Bachelor’s degree in a computer science, engineering, or related field with 7+ years of experience, or Master’s with 6+ years, or PhD with 4+ years.
• 4 years of management or leadership experience.
• Learning and growth mindset and customer-focused approach.
• Strong communication skills (interpersonal, verbal, written).
• Proficiency in at least five and mastery in one of six areas: software eng & version control, ML model development, MLOps/CI-CD, Python, generative AI, healthcare.

Responsibilities

• Develop strategic plans for the Data Science Engineering function aligned with org objectives.
• Lead ML engineers to design, build, and operationalize scalable AI/ML solutions with cross-functional partners.
• Evolve MLOps: CI/CD, model deployment, monitoring, lifecycle management for ML systems.
• Architect secure, scalable infrastructure for training, inference, and serving on cloud platforms.
• Promote code quality, testing, observability, reproducibility, and responsible AI practices.
• Partner with IT and data teams to integrate AI/ML into enterprise systems and workflows.
• Oversee budget, allocate resources, and ensure alignment with goals.

Skills

Software engineering

ML model development

MLOps CI/CD

Python

Generative AI

Healthcare domain

Education

Bachelor's degree

Master's degree

PhD

Tools

Docker

Kubernetes

MLflow

Kubeflow

SageMaker

Azure ML

Databricks

Job description

HCSC is seeking a Senior Director for Data Science Engineering to lead ML engineering efforts that operationalize AI/ML at scale. You will guide a team, collaborate with data scientists, product managers, and IT to deploy dependable solutions.

The role emphasizes MLOps, CI/CD, model deployment, and cloud infrastructure, with a hybrid work model requiring 3 days in-office and a focus on healthcare outcomes for members.