Data Software Engineer III - ML Ops

Northwestern Mutual • Milwaukee, WI

1d • Hybrid

About The Position

Northwestern Mutual (NM) is seeking a highly motivated, curious, and passionate software engineer to join their Data Solutions and Enablement department (DSE). This role will focus on building and designing services, data pipelines, automation, and dashboards for the ML Ops platform, and implementing and standardizing practices for traditional and generative artificial intelligence. The DSE department's mission is to unlock and provide analytical insight on core customer and client data to better serve customers, field representatives, and business partners. The successful candidate will collaborate with Data Scientists, Software Engineers, Data Engineers, and Product Owners to unlock data value through predictive analytics, operationalized machine learning, applied AI, and generative AI.

Requirements

• Strong expertise in programming languages for data engineering.
• Experience with data processing frameworks and Kubernetes.
• Proficiency with cloud platforms (e.g., AWS, Azure, Google Cloud) and data visualization tools.
• Understanding of machine learning concepts.
• Expertise in CI/ML/CD processes and version control.
• Expertise in source code management using Git and GitFlow.
• Strong understanding of CI/CD processes and tools (e.g., Jenkins, GitLab CI/CD, CircleCI) and experience with artifact repositories (e.g., Nexus, Artifactory).
• Strong understanding of agile methodologies and experience in an agile development environment.
• Proficiency with databases and SQL from RDBMS (Postgres, SQL Server, MySql etc.) or big data platforms (Databricks, Spark, Redshift, Snowflake, Big Query etc).
• Familiarity and experience with basic ML algorithms, LLMs, and GenAI/Agentic concepts.
• Understanding of basic tools and libraries common to data science, AI and ML. e.g. ML Flow, Pandas/Numpy/Sklearn, PyTorch/TensorFlow, or LlamaIndex/LangChain/LangGraph OR a strong mathematical and computer science background.
• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.

Nice To Haves

• Curiosity is expected, welcome, and rewarded.
• Passionate about continuous learning and problem solving.
• Collaborate and work creatively every day.

Responsibilities

• Building and standardizing services and patterns in Python and Java to enable model deployment, training, inference, and monitoring.
• Building services and automation to streamline and manage the stages of the AI/ML life cycle and model governance.
• Develop reliable data pipelines that transform and aggregate data from NM’s source systems and data platforms.
• Establish and maintain NM’s data science, ML and AI platforms, with a focus on rapid iteration and operational deployment of predictive models, and cost management of workloads.
• Integrating various ML Ops platforms together such as Databricks, AWS Sagemaker, AWS Bedrock.
• Establish a feature store of curated metrics, attributes, and features for ML models.
• Collaborate closely with data scientists, DevOps Engineers, and enterprise infrastructure teams to enable automation and monitoring across the machine learning lifecycle.
• Develop ML model monitoring pipelines for model performance, data quality, and gen AI evaluation, tracing, and metrics.
• Architect and develop scalable data pipelines using advanced programming skills.
• Gather and translate data requirements into technical solutions.
• Optimize sophisticated data integration and transformation processes.
• Enhance existing systems for performance and scalability.
• Mentor junior engineers and oversee CI/CD pipelines.

Benefits

• Financial security for over 169 years
• Distinctive, whole-picture planning approach including both insurance and investments
• Personalized digital experience and groundbreaking technology
• Competitive compensation
• Opportunities for growth and development

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level