Role: ML DevOps Engineer
Location: Chicago, IL
Experience: 8+ Years
What are we looking for?
We need a DevOps Engineer with strong MLOps experience who can deploy, manage, and maintain Machine Learning and AI models in cloud environments.
The candidate should know how to take an ML model developed by Data Scientists and make it ready to run reliably in a live production environment.
Must-Have Skills
- 5+ years of overall IT experience.
- 3+ years of MLOps or ML-focused DevOps experience.
- Strong experience in at least one cloud: AWS / Azure / GCP.
- MLOps tools: MLflow, Kubeflow, SageMaker, Azure ML, or Databricks.
- Docker and Kubernetes.
- CI/CD: Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
- Terraform or CloudFormation.
- Python and Bash scripting.
- Monitoring tools: Prometheus, Grafana, Datadog, or CloudWatch.
- Understanding of deploying and managing ML models in production.
Good to Have
- Experience with Generative AI and LLM deployments.
- Experience with model serving and API gateways.
- AWS or Azure certifications.
- Banking, finance, or other regulated industry experience.
- Large enterprise/client-facing experience.
Best-fit candidate: An MLOps Engineer or ML-focused DevOps Engineer who has hands-on experience deploying ML models into production using cloud, Docker, Kubernetes, CI/CD, and MLOps tools.