Job Summary

We are seeking an experienced MLOps Engineer to design, automate, and manage scalable machine learning pipelines. The ideal candidate will have expertise in Amazon SageMaker, AWS, CI/CD, Docker, Kubernetes, and Infrastructure as Code.

Key Responsibilities

Design and maintain end-to-end MLOps pipelines.

Build CI/CD pipelines for ML workflows using SageMaker Pipelines, Git, and Terraform/CloudFormation.

Deploy, monitor, and manage ML models on Amazon SageMaker.

Implement model monitoring for performance, drift, bias, and latency.

Manage containerized workloads using Docker and Amazon ECS/EKS.

Collaborate with Data Scientists, ML Engineers, and DevOps teams.

Required Skills

4–8 years of experience in MLOps or Machine Learning Engineering.

Hands-on experience with Amazon SageMaker and ML deployment pipelines.

Strong knowledge of AWS, Docker, Kubernetes (ECS/EKS), Terraform, CloudFormation, Git, and CI/CD.

Experience with model monitoring, versioning, and automation.

Solid scripting skills in Python.

📌 MLOps Engineer (India)
🏢 bytespoke
📍 India