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Senior MLOps Engineer (Chicago, IL)

machine learning technologies llc • United State
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AI Summary

Design, deploy, and optimize end-to-end MLOps pipelines for model development, deployment, and monitoring in production environments. Lead CI/CD/CT workflows, cloud infrastructure, and scalable ML systems across AWS, Azure, or GCP. Collaborate with data scientists to enhance model performance and operational efficiency.

Key Highlights
End-to-end MLOps pipeline ownership for model lifecycle (development, deployment, monitoring)
Hands-on expertise in CI/CD/CT pipelines, Docker, Kubernetes, and cloud platforms (AWS/Azure/GCP)
Focus on model versioning, drift detection, and scalable ML infrastructure with strong DevOps and observability skills

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Key Responsibilities
Design and maintain end-to-end MLOps pipelines for model development, training, deployment, and monitoring.
Build and manage CI/CD/CT pipelines for automated model testing, validation, deployment, and retraining using tools like Jenkins, GitHub Actions, or Azure DevOps.
Deploy and manage ML models in production environments across cloud platforms (AWS, Azure, or GCP) while ensuring scalability, security, and cost optimization.
Implement model versioning, experiment tracking, and artifact management using frameworks like MLflow, Kubeflow, or Metaflow.
Automate infrastructure provisioning and configuration management using Terraform, Ansible, or similar IaC tools.
Monitor model performance, detect data/model drift, and ensure system reliability and observability using Prometheus, Grafana, or ELK Stack.
Collaborate with Data Scientists and ML Engineers to optimize deployment workflows and troubleshoot production issues.
Technical Skills Required
Machine Learning Operations (MLOps) Containerization (Docker) Cloud Platforms (AWS/Azure/GCP)

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Nice to Have
Experience with GPU-based workloads and ML model optimization
Familiarity with feature stores and data orchestration tools (e.g., Airflow)
Knowledge of LLMOps, GenAI deployment, and serving frameworks
Understanding of security, governance, and compliance practices for ML systems

Job Description

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Job Overview
  • Job ID:

J53607
  • Job Title:

MLOps Engineer
  • Location:

Chicago, IL
  • Duration:

18 Months + Extension
  • Domain Exposure:

Utilities/ Energy
  • Work Authorization:

US Citizen,Green Card,OPT-EAD,CPT,H-1B,H4-EAD,L2-EAD,GC-EAD
  • Client:

To Be Discussed Later
  • Employment Type:

W-2, 1099, C2CView All JobsSimilar Jobs
  • Cloud MLOps Engineer - Dallas, TX

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Job Overview
Posted Oct 31, 2026
Employment Full-time
Experience Not Applicable
Location United State
Category Devops
Company machine learning technologies llc
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