Hiring for a ML DevOps Engineer (MLOps Engineer)

Hi,

 

Position: ML DevOps Engineer (MLOps Engineer)
Location: Chicago, IL

Job Overview

We are looking for an experienced ML DevOps Engineer (MLOps Engineer) to design, build, deploy, automate, and maintain scalable Machine Learning infrastructure and production-grade ML pipelines. The ideal candidate will have strong expertise in DevOps, cloud infrastructure, CI/CD automation, containerization, Kubernetes, and machine learning lifecycle management.

The candidate will work closely with Data Scientists, Machine Learning Engineers, and Software Engineers to streamline the development-to-production lifecycle of ML models, ensuring scalability, reliability, performance, and continuous delivery.

 

Key Responsibilities

• Design, develop, 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.
• Deploy and manage machine learning models in production environments across cloud platforms.
• Implement model versioning, experiment tracking, model registries, and artifact management.
• Build and maintain containerized ML applications using Docker and Kubernetes.
• Automate infrastructure provisioning and configuration management using Terraform, Ansible, or similar tools.
• Implement model monitoring, performance tracking, data drift detection, and model drift detection.
• Collaborate with Data Scientists and ML Engineers to optimize model deployment workflows.
• Manage cloud infrastructure and services across AWS, Azure, or GCP.
• Ensure system reliability, scalability, security, and cost optimization for ML workloads.
• Troubleshoot production issues and continuously improve ML deployment and operational processes.

 

Required Technical Skills

1. MLOps & Machine Learning

• Hands-on experience with MLOps frameworks and tools.
• Experience managing the complete ML lifecycle.
• ML model deployment, monitoring, and versioning.
• Familiarity with MLflow, Kubeflow, or Metaflow.
• Understanding of Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

2. DevOps & CI/CD

• Strong experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps.
• Hands-on experience with Docker and Kubernetes.
• Infrastructure as Code (IaC) using Terraform, CloudFormation, or Ansible.
• Experience with Git, automation scripting, and deployment pipelines.

3. Cloud Platforms

• Strong experience with at least one major cloud platform:
• AWS (SageMaker, EKS, S3, EC2, Lambda)
• Microsoft Azure (Azure ML, AKS, Azure DevOps)
• Google Cloud Platform (Vertex AI, GKE, Cloud Storage)

4. Monitoring & Observability

• Experience with Prometheus, Grafana, ELK Stack, or similar tools.
• Monitoring model performance, latency, availability, and resource utilization.
• Understanding of logging, alerting, and production troubleshooting.

5. Programming & Scripting

• Strong Python scripting skills.
• Familiarity with Bash or Shell scripting.
• Working knowledge of APIs, REST services, and microservices architecture.

Preferred Qualifications

• Experience building scalable ML infrastructure and distributed training environments.
• Familiarity with feature stores and data orchestration tools such as Airflow.
• Experience with GPU-based workloads and ML model optimization.
• Understanding of LLMOps, GenAI deployment, and serving frameworks.
• Knowledge of security, governance, and compliance practices for ML systems.

 

Ideal Candidate Profile

The ideal candidate should have a strong combination of DevOps + Cloud + Machine Learning deployment experience. We are particularly interested in professionals who have moved ML models from development environments into scalable, production-ready systems.

 

Keywords for Recruitment

MLOps, ML DevOps, Machine Learning Operations, ML Model Deployment, MLflow, Kubeflow, Kubernetes, Docker, Python, AWS SageMaker, Azure ML, Vertex AI, CI/CD, Terraform, Jenkins, Model Monitoring, Model Registry, Infrastructure as Code, LLMOps.

 

 

Arjun Bhatt SR. Recuriter www.noviainfotech.com

E: arjun.b@noviainfotech.com M: (972) 961 2004 A: 30 N Gould Street, Suite R, Sheridan, WY 82801 Linkedin: linkedin.com/in/arjun-bhatt-3a86001b5

 

 

 

 

 

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