Engineering Manager-AI/ML (Delhi)

Role & responsibilities - Lead and manage a team of Data Scientists and ML Engineers in designing, developing, and deploying AI/ML and Generative AI applications. - Drive the end-to-end lifecycle of ML solutions including data preprocessing, model development, evaluation, deployment, and monitoring in production. - Design and implement scalable, secure, and high-performing AI/ML architectures and pipelines on cloud platforms such as GCP, AWS, or Azure. - Develop and fine-tune Large Language Models (LLMs) and build RAG (Retrieval-Augmented Generation) based GenAI solutions for business use cases. - Perform prompt engineering and optimization to improve LLM accuracy, personalization, and contextual understanding. - Collaborate with product managers, architects, and cross-functional teams to define AI/ML strategies and integrate models into enterprise applications. - Build and maintain data pipelines involving data ingestion, transformation, and feature engineering for model training and evaluation. - Provide technical mentorship, code reviews, and career guidance to team members to build solid ML and data engineering capabilities. - Ensure the reliability, scalability, and cost-effectiveness of AI/ML solutions using best practices in software design and DevOps. - Stay updated with the latest research and advancements in AI, ML, NLP, Vision AI, and Generative AI technologies to drive innovation. - Oversee project planning, estimation, and timely delivery of AI/ML initiatives with high quality and business alignment. - Collaborate with customers to understand requirements, design proof of concepts (POCs), and deliver end-to-end production-ready AI/ML solutions. Preferred candidate profile - Experience: 8 to 12 years of total IT experience, with at least 5+ years in AI/ML solution design and deployment. - Leadership: Minimum 2 years of experience leading ML or Data Science teams (4+ members). - Technical Expertise: Strong hands-on experience in Machine Learning, Deep Learning, NLP, Vision AI, and Generative AI (RAG, LLM fine-tuning, Prompt Engineering). - Cloud Knowledge: Practical exposure to Google Cloud Platform (GCP) or equivalent (AWS / Azure) for building and deploying ML pipelines. - Programming Skills: Proficiency in Python, Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, LangChain, and XGBoost. - Architecture Skills: Proven ability to design and implement secure, scalable, and high-performance AI/ML architectures. - Educational Qualification: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. - Certifications (Good to Have): Google Cloud ML Engineer / TensorFlow Developer Certification. - Soft Skills: Excellent communication, analytical thinking, stakeholder management, and team collaboration skills. Role & responsibilities - Lead and manage a team of Data Scientists and ML Engineers in designing, developing, and deploying AI/ML and Generative AI applications. - Drive the end-to-end lifecycle of ML solutions including data preprocessing, model development, evaluation, deployment, and monitoring in production. - Design and implement scalable, secure, and high-performing AI/ML architectures and pipelines on cloud platforms such as GCP, AWS, or Azure. - Develop and fine-tune Large Language Models (LLMs) and build RAG (Retrieval-Augmented Generation) based GenAI solutions for business use cases. - Perform prompt engineering and optimization to improve LLM accuracy, personalization, and contextual understanding. - Collaborate with product managers, architects, and cross-functional teams to define AI/ML strategies and integrate models into enterprise applications. - Build and maintain data pipelines involving data ingestion, transformation, and feature engineering for model training and evaluation. - Provide technical mentorship, code reviews, and career guidance to team members to build solid ML and data engineering capabilities. - Ensure the reliability, scalability, and cost-effectiveness of AI/ML solutions using best practices in software design and DevOps. - Stay updated with the latest research and advancements in AI, ML, NLP, Vision AI, and Generative AI technologies to drive innovation. - Oversee project planning, estimation, and timely delivery of AI/ML initiatives with high quality and business alignment. - Collaborate with customers to understand requirements, design proof of concepts (POCs), and deliver end-to-end production-ready AI/ML solutions. Preferred candidate profile - Experience: 8 to 12 years of total IT experience, with at least 5+ years in AI/ML solution design and deployment. - Leadership: Minimum 2 years of experience leading ML or Data Science teams (4+ members). - Technical Expertise: Strong hands-on experience in Machine Learning, Deep Learning, NLP, Vision AI, and Generative AI (RAG, LLM fine-tuning, Prompt Engineering). - Cloud Knowledg