The role involves designing, developing, and deploying advanced machine learning and generative AI systems for global retail and manufacturing clients. The practitioner will architect LLM-powered applications and agentic workflows that integrate models, tools, and business logic to solve complex analytical problems. Responsibilities include transitioning AI capabilities from prototypes to secure, production-grade systems while defining standards for model quality and lifecycle management. The individual will act as a technical leader, collaborating across product and engineering teams to influence AI architecture and best practices. Additionally, the role requires mentoring other data scientists and staying current with advancements in AI frameworks and cloud-native architectures.

Candidates must hold a Master’s or PhD in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, or a related field. A minimum of 10 years of experience in building and deploying machine learning and AI systems in production environments is required. Applicants must possess advanced proficiency in Python, SQL, and PySpark, along with hands-on experience in cloud-based MLOps and LLMOps practices. Furthermore, the role necessitates deep expertise in generative AI, including prompt engineering, RAG, and agentic system architectures.