Data Software Engineer III - ML Ops

Location: Hybrid in Milwaukee, Wisconsin, United States; 3 days onsite at the downtown Milwaukee corporate office.

Salary: $108,160–$162,240 per year.

Company

hirify.global provides insurance, investment, financial planning, and digital technology services focused on helping clients achieve financial security.

What you will do

• Build and standardize Python and Java services for model deployment, training, inference, and monitoring.
• Develop automation for AI/ML lifecycle management, governance, and CI/CD-first operational deployment.
• Architect reliable data pipelines that transform and aggregate data from source systems and data platforms.
• Establish and maintain ML and AI platforms, including integrations with Databricks, AWS SageMaker, and AWS Bedrock.
• Build a feature store and monitoring pipelines for model performance, data quality, generative AI evaluation, tracing, and metrics.
• Collaborate with data scientists, DevOps engineers, software engineers, data engineers, product owners, and infrastructure teams.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
• Strong programming and data engineering expertise, including Python and Java.
• Experience with data processing frameworks, Kubernetes, databases, SQL, cloud platforms, and data visualization tools.
• Understanding of machine learning concepts, LLMs, generative AI, and agentic concepts.
• Expertise with CI/CD, Git, GitFlow, source code management, and artifact repositories such as Nexus or Artifactory.
• Experience working in an agile development environment and ability to mentor junior engineers.

Culture & Benefits

• Collaborative work with data scientists, engineers, product owners, and enterprise infrastructure teams.
• Focus on continuous learning, curiosity, creative problem solving, and process improvement.
• Work in a financial services organization with a long-term focus on client security and technology.
• Compensation is based on skills, experience, market conditions, and work location.