Location: Chicago, IL (Hybrid – 2 to 3 days onsite, no exceptions)
5+ years of software engineering experience
Strong programming skills in Python (Java/Golang/C++ also acceptable)
Hands-on experience with MLOps frameworks (MLflow, Kubeflow, etc.)
Experience building and deploying ML pipelines on AWS
Strong knowledge of CI/CD, DevOps, Git/GitHub, Azure DevOps
Experience with Docker and Kubernetes
Ability to support ML model deployment, monitoring, automation, and troubleshooting
Strong communication and collaboration skills
Nice to Have:
Seldon, Kubeflow, MLFlow inference systems
Terraform or CloudFormation
Helm/Helmfile
Observability tools such as Evidently AI
Responsibilities:
Build and support enterprise MLOps platform
Develop scalable ML deployment pipelines
Automate model testing, validation, deployment, and monitoring
Work with Data Science teams to operationalize ML models
Create documentation, user training, and platform best practices

Machine Learning Engineer

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