MLOps Intern: Build Pipelines & Deploy Models (Hybrid)

American Family Insurance; Madison, Northern (WI, KY); Hybrid; USD 34,000 - 41,000; Full time

Benefits offered by this job

New Employee Orientation

Health, dental, vision and wellbeing

401(k) contribution

Pension plan

Paid holidays

Paid time off

Student loan repayment

Paid-family leave

Job summary

American Family Insurance in Madison, Wisconsin is seeking an ML Ops Engineering intern. This on-site hybrid role offers exposure to ML Ops—Model Registry and Feature Store—and collaboration with data science teams to deploy models.

You will develop features, maintain and monitor MLOps tools, and present findings to management. Applicants are pursuing a degree in CS/SE/DS with Python experience and a willingness to learn.

Qualifications

• Pursuing a degree in CS, SWE, CE, DS, AI, ML or related field.
• Basic to intermediate software development skills and willingness to learn.
• Experience with Python through coursework or projects.
• Familiarity with cloud platforms, CI/CD, DevOps or MLOps concepts is a plus.
• Strong analytical, problem-solving, communication and teamwork skills.
• Participation in relevant projects is preferred.

Responsibilities

• Develop understanding of the organization's business environment and culture.
• Contribute ideas and solutions to evolving business and technical needs.
• Assist in enhancing MLOps frameworks by developing and testing new features.
• Support maintenance, monitoring, and improvement of MLOps tools and platforms.
• Help modify and optimize ML pipelines for various use cases.
• Collaborate with team members on technical projects and tasks.
• Present project work, findings, and recommendations to management.

Skills

Python

Cloud platforms

CI/CD

DevOps

MLOps

Analytical skills

Communication

Teamwork

Learning mindset

Education

Bachelor/Master/PhD in CS/SE/CE/DS/AI/ML

Job description

American Family Insurance in Madison, Wisconsin is seeking an ML Ops Engineering intern. This on-site hybrid role offers exposure to ML Ops—Model Registry and Feature Store—and collaboration with data science teams to deploy models.

You will develop features, maintain and monitor MLOps tools, and present findings to management. Applicants are pursuing a degree in CS/SE/DS with Python experience and a willingness to learn.