ML DevOps Engineer, Chicago, IL
TROR LLC
Chicago, IL, United States
6 days ago
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Role details
Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source
Tech stack
Amazon Web Services
Microsoft Azure
Bash Shell
Cloud Computing
Continuous Integration
DevOps
Github
Monitoring of Systems
Python (Programming Language)
Machine Learning
Prometheus
Azure Machine Learning
+17 more
Datadog
Google Cloud
Cloud Platform System
Large Language Models
Grafana
Generative AI
Cloudformation
Gitlab-ci
Kubernetes
Information Technology
Machine Learning Operations
Cloudwatch
Api Gateway
Terraform
Docker
Jenkins
Databricks
Requirements
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 / Google Cloud Platform.
- 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.
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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.
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