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
- Strong 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 career growth opportunities
