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Technical / Behavioural Expertise in Machine Learning (ML) and Artificial Intelligence (AI): - Ability to interpret business challenges and convert them into ML-based problem statements, followed by designing and executing complete end-to-end solutions. - Extensive hands-on experience in leveraging data mining and ML methodologies to address complex, real-world business scenarios. - Proficient in working with diverse data types structured, unstructured, audio, and both static and streaming datasets. - Advanced proficiency in Natural Language Processing (NLP) and/or Natural Language Understanding (NLU) techniques is essential. - Solid command of Generative AI and Large Language Models (LLMs), including pre-training, fine-tuning, domain adaptation, and agent-based workflow design. - Demonstrated ability to stay current with the latest research in ML/GenAI and apply state-of-the-art approaches to practical use cases within the organization. - Skilled in clearly articulating design decisions, trade-offs, and outcomes to both technical and business stakeholders. Behavioural / Soft Skills - Excellent verbal and written communication skills. - Highly driven and goal-oriented, with a strong sense of ownership. - Capable of working independently with minimal supervision. - Effective collaborator in multidisciplinary and cross-functional teams. - Able to coach, mentor, and support the growth of junior team members. Additional Skills - Advanced expertise in Python programming. - Experience in developing and deploying ML models using cloud services such as AWS SageMaker. - Familiar with Git-based workflows and CI/CD practices for collaborative, version-controlled development. - Ability to structure and maintain clean, modular code using functional programming principles; exposure to statically typed functional languages is an advantage. - Comfortable interacting with various data systems writing REST APIs, SQL queries, and PySpark scripts as needed. - Experience with containerization technologies such as Docker. Desirable Skills - Understanding of recommendation systems and reinforcement learning frameworks. - Practical experience with frameworks such as LangChain, LangGraph, or LlamaIndex. .