Education and Experience: A degree (Masters preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields. Minimum 5+ years of hands-on experience in AI/ML or Data Science, preferably in real industry settings, with a track record of building data products that have positively impacted customer satisfaction and revenue growth. Technical Skills: Proficiency in a wide range of Machine Learning techniques and algorithms, with the ability to apply advanced analytics methods, including Bayesian statistics, clustering, text analysis, time series analysis, and neural networks on large-scale datasets. Expertise in at least one specialized area of application, such as Computer Vision or Natural Language Processing (NLP). (NLP Expertise preferred) Strong programming skills in Python, including expertise in the data ecosystem (Numpy, Scipy, Pandas, etc.) or equivalent skills in languages like R, Java, Scala, or Julia, with a focus on producing production-quality code. Hands-on experience with popular ML frameworks like Scikit-Learn, PyTorch, or TensorFlow. Expertise with Generative AI and Large Language Models (LLMs) along with their implementation in real-life applications. Experience building end-to-end ML systems (MLOps). Experience in deploying code in web frameworks such as Flask, FastAPI or Django. Experience working in a cloud environment like AWS, Azure, or GCP for ML work. Good grasp of SQL/NoSQL databases and scripting skills, particularly within analytics platforms and data warehouses. Good grasp of software engineering concepts (SDLC, Version Control, CI/CD, Containerization, Scalability and so on), programming concepts, and tools/platforms like Git and Docker. Bonus: Experience with Big Data technologies such as Apache Spark, Kafka, Kinesis, and cloud-based ML platforms like AWS SageMaker or GCP ML Engine. Bonus: Experience with data visualization and dashboard tools like Tableau or Power BI. Soft Skills: Highly motivated, self-driven, entrepreneurial mindset, and capable of solving complex analytical problems under high-pressure situations. Ability to work with cross-functional and cross-regional teams. Ability to lead a team of Data/AI professionals and work with senior management, technological experts, and the product team. Excellent written and verbal communication skills, comfortable with client communication. Good leadership skills - ability to motivate and mentor team members, ability to plan and make sound decisions, ability to negotiate tactfully with the client and team. Results-oriented, customer-focused with a passion for resolving tough technical and operational challenges. Possess excellent analytical and problem-solving abilities. Good documentation skills. Experienced with Agile methodologies like Scrum/Kanban