Staff Data Scientist – AI/ML, Generative AI & Agentic Systems

About the role

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape. Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality. Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

We are seeking a highly skilled and forward-thinking Staff Data Scientist with 5–7 years of experience in AI/ML, Generative AI, and Agentic AI systems to join our Advanced Supply Chain Analytics team. This role will focus on developing intelligent, autonomous, and self-orchestrating systems that enhance forecasting, planning, and operational decision-making across the global supply chain. The ideal candidate will have hands-on experience with LLMs, LangChain, multi-agent frameworks, and cloud-based ML engineering (AWS). You will design scalable, production-grade AI solutions, collaborating closely with cross-functional teams to accelerate our digital and supply chain transformation journey.

Responsibilities

• Design, build, and deploy AI/ML models for Supply Chain Planning (Demand Planning, Product Planning, Capacity planning, Inventory optimization, and production scheduling).
• Develop multi-agent and generative AI-powered systems (using LLMs and frameworks like LangChain, AutoGen, CrewAI) to enable real-time decision orchestration and intelligent automation.
• Prototype intelligent assistants that interpret complex workflows, automate tasks, and generate data-driven recommendations for supply chain planners.
• Implement autonomous agentic workflows that integrate