Lead Machine Learning Engineer (Python, GenAI, MLOps) (Bengaluru)

About the Role: We are seeking a senior technical lead to architect, develop, and deploy scalable Machine Learning and Generative AI solutions. This role involves endtoend ownership of the model lifecycle, driving MLOps excellence, enabling cloudnative deployments, and collaborating crossfunctionally to deliver highimpact AI initiatives. What You will Do: Lead development, optimization, and deployment of ML and GenAI models for real-time, streaming and batch use cases. Evaluation and picking LLM and embedding models for various use cases. Ingestion of structured and unstructured data sources, storing them to vector databases. Build and manage end-to-end agentic workflows for data retrieval, reasoning, and insight generation. Build and manage end-to-end MLOps pipelines with Sagemaker, Airflow, or similar platforms. Collaborate with engineers, data scientists, and stakeholders to gather requirements, ideate, and integrate AI solutions. Enhance model accuracy and performance through data quality improvements and analysis. Deploy scalable, cloud-native ML workloads on AWS using Docker, Kubernetes. Mentor junior engineers on ML best practices. Evaluate and integrate third-party tools, libraries, and products. Develop and manage robust CI/CD pipelines. Provide technical leadership and stay current with ML advancements. What You Bring: 5 years of skilled experience in Python development and machine learning. Strong understanding of MLOps practices and tools. Experience deploying ML models in production environments. Familiarity with TensorFlow, PyTor About the Role: We are seeking a senior technical lead to architect, develop, and deploy scalable Machine Learning and Generative AI solutions. This role involves endtoend ownership of the model lifecycle, driving MLOps excellence, enabling cloudnative deployments, and collaborating crossfunctionally to deliver highimpact AI initiatives. What You will Do: Lead development, optimization, and deployment of ML and GenAI models for real-time, streaming and batch use cases. Evaluation and picking LLM and embedding models for various use cases. Ingestion of structured and unstructured data sources, storing them to vector databases. Build and manage end-to-end agentic workflows for data retrieval, reasoning, and insight generation. Build and manage end-to-end MLOps pipelines with Sagemaker, Airflow, or similar platforms. Collaborate with engineers, data scientists, and stakeholders to gather requirements, ideate, and integrate AI solutions. Enhance model accuracy and performance through data quality improvements and analysis. Deploy scalable, cloud-native ML workloads on AWS using Docker, Kubernetes. Mentor junior engineers on ML best practices. Evaluate and integrate third-party tools, libraries, and products. Develop and manage robust CI/CD pipelines. Provide technical leadership and stay current with ML advancements. What You Bring: 5 years of skilled experience in Python development and machine learning. Strong understanding of MLOps practices and tools. Experience deploying ML models in production environments. Familiarity with TensorFlow, PyTor