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Hexaware Technologies is seeking a senior AI/ML leader to design, develop and deploy advanced AI solutions. You will define problems, acquire data, build models, deploy in production, and ensure ongoing optimization while mentoring junior developers.
Ideal candidates will have 15+ years in IT with 5+ focused on AI/ML, Generative AI or LLM-based solutions, and expert Python skills. Collaboration with data scientists and engineers is essential.
Design, develop, and deliver innovative AI and ML solutions that effectively address complex business challenges.
Lead the complete AI development lifecycle, including problem definition, data acquisition, model development, deployment, and ongoing maintenance. Collaborate closely with cross-functional teams to gather and analyze business requirements, translating them into scalable AI solutions.
Stay current with emerging AI/ML technologies, frameworks, and industry best practices to continuously enhance solution quality.
Mentor and guide junior AI developers, fostering skill development and knowledge sharing within the team.
Conduct rigorous code reviews to ensure high standards of code quality, scalability, and performance in AI applications.
Partner with data scientists and engineers to preprocess, clean, and prepare data for modeling.
Evaluate and select the most appropriate AI and ML algorithms tailored to specific business needs.
Deploy AI models in production environments, continuously monitoring and optimizing their performance.
Implement robust data privacy and security protocols within AI solutions to ensure compliance and protect sensitive information.
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
Experience: Minimum 15 years in IT with at least 5 years focused on AI/ML, Generative AI, or Large Language Model (LLM)-based solution development. Programming: Expert-level proficiency in Python. Generative AI Expertise Deep experience with Large Language Models (LLMs) and advanced prompt engineering techniques.
Design and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced knowledge retrieval. Integration proficiency with vector databases such as Pinecone, Weaviate, FAISS, and Milvus.