AI/ML Lead (Applied AI/ML) (Bengaluru)

Job Title: AI/ML Lead (Applied AI/ML) Experience: 8+ Years Location: Remote Notice Period: Immediate Joiner Position Overview We are seeking an experienced and highly skilled Applied AI/ML Lead to lead the design, development, and deployment of AI/ML solutions for real -world business use cases. This role focuses on translating AI research and models into production -ready, scalable solutions that deliver measurable business impact. As an AI/ML Lead, you will collaborate closely with cross -functional teams including Data Analytics, Engineering, and Product, influence AI -driven business strategies, and mentor a growing AI/ML team while staying current with emerging AI technologies. Roles & Responsibilities - Lead the development, deployment, and optimization of AI/ML models for customer -facing applications. - Drive AI initiatives focused on personalization, recommendations, and predictive analytics. - Collaborate with Data Analytics, Data Engineering, and Development teams to integrate AI models into production systems. - Design and implement AI solutions using clustering, segmentation, and scoring techniques. - Ensure data readiness, quality, and pipeline reliability for AI/ML workloads. - Oversee the development of AI/ML -based features and capabilities aligned with business goals. - Implement AIOps practices to monitor model performance and reduce MTTR (Mean Time to Resolution). - Mentor and provide technical leadership to junior AI/ML engineers and data scientists. - Continuously evaluate and adopt new AI/ML technologies and best practices. Must -Have Skills - 8+ years of experience in AI/ML, with at least 3 years in a leadership or technical lead role. - Strong experience in applying AI/ML to business problems, especially customer experience and personalization. - Hands -on expertise with TensorFlow, PyTorch, and scikit -learn. - Strong proficiency in Python for AI/ML development and deployment. - Experience integrating AI/ML models with cloud platforms (AWS preferred). - Hands -on exposure to AWS AI/ML services such as SageMaker or equivalent. - Deep understanding of customer segmentation, scoring, and recommendation systems. - Experience working with real -time data systems and pipelines (e.g., Kafka). - Solid understanding of end -to -end ML lifecycle management from experimentation to production. Good to Have - Experience with MinIO and S3 for large -scale data storage. - Exposure to workflow orchestration tools like Apache Airflow. - Knowledge or hands -on experience with LLMs (Large Language Models) and RAG (Retrieval -Augmented Generation). - Experience in automating AI/ML pipelines and deployments. Qualifications - Bachelors degree in Computer Science, Engineering, or a related technical discipline. .