Lead Data Engineer — ML & AI Ops

Northwestern Mutual Investment Services, LLC; Milwaukee (WI); Hybrid; USD 108,000 - 187,000; Full time

Job summary

Northwestern Mutual Investment Services, LLC is seeking an Assistant Director, Data Software Engineering – AI/ML Ops to lead the design of data systems, pipelines, and dashboards for our ML Ops platform. You will collaborate with data scientists and engineers to deploy predictive analytics and generative AI solutions, and to standardize AI/ML practices across teams.

You will help establish data pipelines, model monitoring, and platform governance while leveraging Python, Java, Databricks, AWS

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• Strong programming experience in data engineering and software development.
• Experience with data processing frameworks and Kubernetes.
• Proficiency with cloud platforms (AWS, Azure, Google Cloud) and data visualization tools.
• Understanding of machine learning concepts and CI/CD practices.

Responsibilities

• Architect and develop scalable data pipelines using advanced programming skills.
• Gather and translate data requirements into technical solutions.
• Optimize complex data integration and transformation processes.
• Mentor junior engineers and oversee CI/CD pipelines.
• Develop ML model monitoring pipelines and data quality checks.

Skills

Python

Java

CI/CD

Git/GitFlow

Analytical Thinking

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Databricks

AWS

Sagemaker

Bedrock

Kubernetes

Spark

Postgres/SQL

Job description

Northwestern Mutual Investment Services, LLC is seeking an Assistant Director, Data Software Engineering – AI/ML Ops to lead the design of data systems, pipelines, and dashboards for our ML Ops platform. You will collaborate with data scientists and engineers to deploy predictive analytics and generative AI solutions, and to standardize AI/ML practices across teams.

You will help establish data pipelines, model monitoring, and platform governance while leveraging Python, Java, Databricks, AWS