MLOps Engineer - Build & Deploy Scalable ML Pipelines

Artifintech; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Artifintech is seeking an experienced MLOps Engineer to design and manage end-to-end ML pipelines, from data to deployment and monitoring. You will build CI/CD workflows, deploy models to cloud environments, and ensure reproducibility with versioning and artifact management.

You will collaborate with data scientists and ML engineers, automate infrastructure with Terraform/Ansible, and maintain scalable, secure ML platforms across AWS, Azure, or GCP.

Qualifications

• Hands-on experience with end-to-end MLOps pipelines and tools.
• Experience managing the complete ML lifecycle from data prep to deployment.
• ML model deployment, monitoring, and versioning.
• Familiarity with MLflow, Kubeflow, or Metaflow.
• Strong Python scripting and ML framework knowledge (TensorFlow, PyTorch, Scikit-learn).

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 ML 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.
• 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.

Skills

MLOps

ML lifecycle

Model deployment

Python

Bash

REST APIs

CI/CD

Docker

Kubernetes

Terraform/Ansible

Cloud platforms

Monitoring

Security/Governance

GPU/Distributed training

LLMOps/GenAI

Airflow/Feature stores

Tools

MLflow

Kubeflow

Metaflow

Docker

Kubernetes

Terraform

Ansible

Git

Airflow

Prometheus

Grafana

ELK

Job description

Artifintech is seeking an experienced MLOps Engineer to design and manage end-to-end ML pipelines, from data to deployment and monitoring. You will build CI/CD workflows, deploy models to cloud environments, and ensure reproducibility with versioning and artifact management.

You will collaborate with data scientists and ML engineers, automate infrastructure with Terraform/Ansible, and maintain scalable, secure ML platforms across AWS, Azure, or GCP.