MLOps Engineer - Immediate Joiners

Job Summary

We are seeking an experienced MLOps Engineer with 4+ years of hands-on experience in building, deploying, and maintaining production-grade machine learning systems. This is a contract-based role, and we are specifically looking for immediate joiners. The ideal candidate must have strong expertise in Databricks, end-to-end ML lifecycle management, and model deployment in scalable production environments.

Key Responsibilities

Design, build, and maintain scalable ML pipelines using Databricks Deploy machine learning models into production environments Manage end-to-end ML lifecycle including experimentation, versioning, deployment, and monitoring Implement CI/CD pipelines for ML workflows Automate model training, testing, and deployment processes Monitor model performance, data drift, and system reliability Optimize performance and cost of ML infrastructure Collaborate with Data Scientists, Data Engineers, and DevOps teams Ensure proper documentation and adherence to MLOps best practices

Required Skills & Experience

4+ years of experience in MLOps / ML Engineering / DevOps for ML systems Strong hands-on experience with Databricks (workspace management, MLflow integration, job orchestration) Proven experience deploying ML models into production (REST APIs, batch inference, real-time serving) Strong proficiency in Python Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch, etc.) Experience with cloud platforms (AWS / Azure / GCP) Hands-on experience with Docker and Kubernetes Experience implementing CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, etc.) Strong understanding of distributed systems and data engineering concepts