AI/ML Lead

Interview location : Face-to-Face (F2F) in Pune, Gurugram, Kolkata, Bangalore & Vadodara

Work Mode: Remote

Experience: Leadership Level

Required Skills

• Strong hands-on experience with Python, Pandas, SQL, data analysis, and feature engineering.
• Expertise in AWS SageMaker, Amazon Bedrock, and cloud-based AI/ML solutions.
• Strong experience with Databricks, MLflow, model lifecycle management, and large-scale data processing.
• Good understanding of MLOps, model deployment, monitoring, drift detection, and model governance.
• Experience with hyperparameter tuning, model validation, performance optimization, and scalable system design.
• Knowledge of Snowflake and modern data architectures.
• Proven experience in technical leadership, team management, and stakeholder communication.

Job Overview

We are looking for an experienced Senior AI/ML Leader to lead the design, development, and deployment of scalable Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and Agentic AI solutions. The ideal candidate should have strong hands-on technical expertise, experience managing technical teams, and the ability to build production-ready AI solutions that deliver measurable business value.

Key Responsibilities

• Define AI/ML strategy, technical architecture, and implementation roadmaps.
• Lead and mentor teams of data scientists, ML engineers, and AI engineers.
• Design and deploy end-to-end machine learning models, including training, evaluation, deployment, and monitoring.
• Implement MLOps practices, including CI/CD pipelines, model versioning, experiment tracking, and model monitoring.
• Develop scalable AI/ML solutions using AWS services, particularly Amazon SageMaker and Amazon Bedrock.
• Work with Databricks, MLflow, Snowflake, and modern cloud data platforms.
• Build and optimize Generative AI and Agentic AI solutions, including RAG, AI agents, and workflow automation.
• Ensure AI systems are scalable, secure, reliable, cost-effective, and compliant with responsible AI practices.
• Collaborate with business, product, data engineering, and cloud teams to deliver AI-driven solutions.