Location: Hyderabad

Experience: 2–5 Years

Employment Type: Full time

About The Role

We are looking for an experienced MLOps Engineer to build, deploy, and maintain scalable machine learning systems. You will work closely with data scientists and engineering teams to operationalize ML models and ensure reliability in production.

Key Responsibilities
Design, build, and manage end-to-end ML pipelines
Deploy and maintain machine learning models in production
Implement CI/CD pipelines for ML workflows
Automate model training, versioning, and deployment processes
Monitor model performance, data drift, and system health
Manage containerized deployments using Docker and Kubernetes
Collaborate with cross-functional teams to improve ML delivery
Ensure best practices in scalability, security, and reliability

Required Skills & Qualifications
2–5 years of experience in MLOps, DevOps, or ML Engineering




Solid proficiency in Python
Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Experience with Docker and Kubernetes
Knowledge of CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.)
Experience with cloud platforms (AWS, Azure, or GCP)
Understanding of ML lifecycle, deployment, and monitoring

Good to Have
Experience with MLflow, Kubeflow, Airflow, or similar tools
Knowledge of data pipelines and ETL processes
Familiarity with infrastructure as code (Terraform, CloudFormation)
Experience with monitoring tools and logging frameworks

What We Offer
Work on real-world, production ML systems
Opportunity to collaborate with AI and data science teams
Continuous learning and growth opportunities opportunities

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