MLOps Engineer | Chennai /Hyderabad | On-site | 3+ Years | Immediate Joiner

Unicorn Workforce; Chennai; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A leading technology consulting firm is seeking an MLOps Engineer to design and maintain scalable machine learning pipelines. The role requires 5-12 years of experience and strong skills in Python, ML frameworks, and CI/CD tools. Located in Chennai, this is a full-time on-site position that offers opportunities to work closely with data scientists and cloud platforms.

Qualifications

• 5-12 years of experience in MLOps or related roles.
• Strong understanding of ML lifecycle management.
• Hands-on experience with container orchestration and cloud platforms.

Responsibilities

• Build, deploy, and manage end-to-end ML pipelines.
• Develop and maintain CI/CD workflows for ML models.
• Manage model versioning, deployment, and scaling in production.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

CI/CD tools

Docker

Kubernetes

AWS Sagemaker

Azure ML

GCP Vertex AI

Problem-solving skills

Tools

GitHub Actions

Jenkins

GitLab CI/CD

Argo

Terraform

CloudFormation

DVC

MLflow

Kubeflow

Job description

Job Description

MLOps Engineer | Chennai / Hyderabad | On-site | 3+ Years | Immediate Joiner

Direct message the job poster from Unicorn Workforce

Job Title: MLOps Engineer

Location: Chennai/Hyderabad

Experience: 5 – 12 Years

Notice Period: Immediate to 30 Days

Job Description

We are seeking an experienced MLOps Engineer to design, implement, and maintain scalable machine learning pipelines and infrastructure. The role requires a strong understanding of ML lifecycle management, CI/CD for ML models, and cloud platforms to ensure seamless integration between data science and production environments.

Key Responsibilities

• Build, deploy, and manage end-to-end ML pipelines from experimentation to production.
• Develop and maintain CI/CD workflows for ML models.
• Automate training, testing, monitoring, and retraining processes.
• Manage model versioning, deployment, and scaling in production environments.
• Ensure observability, logging, and monitoring for ML models and pipelines.
• Collaborate with data scientists, data engineers, and software engineers to deliver robust ML solutions.
• Optimize cost, performance, and reliability of ML infrastructure.

Required Skills

• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with CI/CD tools (GitHub Actions, Jenkins, GitLab CI/CD, Argo).
• Proficiency in Docker, Kubernetes, and container orchestration.
• Experience with cloud platforms (AWS Sagemaker, Azure ML, GCP Vertex AI).
• Knowledge of ML model monitoring, logging, and A/B testing.
• Understanding of data pipelines, ETL, and feature stores.
• Strong problem-solving and debugging skills.

Good to Have

• Experience with infrastructure as code (IaC) using Terraform/CloudFormation.
• Exposure to data versioning tools like DVC, MLflow, or Kubeflow.
• Knowledge of security and compliance in ML systems.

Seniority level

• Associate

Employment type

• Full-time

Job function

• Information Technology

Industries

• Software Development, IT System Custom Software Development, and IT Services and IT Consulting

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