GlobalLogic - MLOps Engineer - Python

MLOps Engineer

Location : Bangalore - Whitefield

Experience : 7 - 10 Years

Employment Type : Full-time

Role Overview :

We are looking for an experienced MLOps Engineer with strong expertise in machine learning engineering, cloud-based ML platforms, and AI/ML model deployment. The ideal candidate will be responsible for building scalable ML pipelines, automating model development and deployment workflows, and enabling reliable productionisation of AI/ML and Generative AI solutions. The role requires hands-on experience with Python, MLOps, Deep Learning, RAG & LLMs, TensorFlow, and Databricks, along with a strong understanding of ML lifecycle management and production environments.

Key Responsibilities :

• Design, build and maintain scalable MLOps pipelines for model development, training, validation and deployment.
• Develop and automate CI/CD workflows for machine learning models and AI applications.
• Deploy, monitor and maintain ML models in production environments.
• Work closely with Data Scientists, ML Engineers, Data Engineers and application teams to productionise machine learning solutions.
• Develop and optimise machine learning workflows using Python and TensorFlow.
• Build and manage data and ML pipelines using Databricks and related technologies.
• Support the development and deployment of Deep Learning models.
• Work on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and other Generative AI use cases.
• Design pipelines for data preparation, feature engineering, model training and inference.
• Implement model versioning, experiment tracking, model validation and lifecycle management.
• Establish monitoring mechanisms for model performance, data quality, drift and system health.
• Optimise ML infrastructure for scalability, reliability and cost efficiency.
• Troubleshoot production issues and continuously improve the reliability of ML systems.
• Ensure security, governance and best practices are followed throughout the ML lifecycle.
• Stay updated with emerging technologies and best practices across MLOps, GenAI and AI engineering.

Required Skills :

• 7 - 12 years of overall experience in MLOps / ML Engineering / AI Engineering.
• Strong hands-on programming experience in Python.
• Strong understanding of MLOps principles and ML lifecycle management.
• Hands-on experience with TensorFlow and Deep Learning frameworks.
• Experience working with LLMs and Generative AI.
• Practical understanding of RAG architectures, embeddings, vector search and retrieval pipelines.
• Strong experience with Databricks and ML/data processing workflows.
• Experience building and managing automated ML pipelines.
• Good understanding of model deployment, monitoring and productionisation.
• Experience with CI/CD, version control and automated deployment practices.
• Strong understanding of data pipelines and data engineering concepts.

Good to Have :

• Experience with cloud platforms such as AWS, Azure or GCP.
• Experience with Docker and Kubernetes.
• Knowledge of MLflow or similar experiment/model lifecycle management tools.
• Experience with vector databases and semantic search.
• Exposure to Agentic AI and AI application development.
• Knowledge of infrastructure-as-code and cloud-native architectures.
• Experience implementing responsible AI, security and governance practices.

Key Competencies :

• Strong problem-solving and analytical skills.
• Ability to work effectively with cross-functional teams.
• Strong communication and stakeholder-management skills.
• Ability to translate AI/ML requirements into scalable production solutions.
• Strong ownership and focus on building reliable, production-ready systems.