MLOps Engineer

A large insurance customer is building a new AI/ML Platform team responsible for operationalizing machine learning across the enterprise. They are seeking an MLOps Engineer to help build, deploy, and support production machine learning infrastructure within AWS. This engineer will partner closely with Data Scientists, Cloud Engineers, and Application teams to productionize ML models, automate deployment pipelines, and establish monitoring, observability, governance, and FinOps best practices. This is a hands-on engineering role focused on building scalable, reliable ML platforms that enable AI solutions to move efficiently from development into production while helping establish standards for a newly formed enterprise AI organization.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:


Required Skills & Experience
• 3-5+ years of experience in AWS Cloud Engineering, DevOps, Platform Engineering, or MLOps.
• Hands-on experience building and deploying ML pipelines in AWS using services such as SageMaker, Lambda, S3, and Step Functions.
• 1+ year supporting production ML systems, including monitoring, troubleshooting, retraining, and operational support.
• Strong Python development experience.
• Experience building and supporting CI/CD pipelines.
• Infrastructure-as-Code experience with Terraform, CloudFormation, or AWS CDK.
• Experience partnering directly with Data Scientists to productionize machine learning models.
• Strong understanding of the ML lifecycle, including deployment, monitoring, observability, retraining, and production support.


Nice to Have Skills & Experience
• Experience with Amazon Bedrock.
• Experience with Docker and containerization technologies.
• Experience with Kubernetes, ECS, and/or EKS.
• Experience with ML observability tools.
• Experience with feature stores and model governance frameworks.
• Experience working in regulated environments such as insurance, healthcare, or financial services.


Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.