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

Requirements

• Expertise in Python, SQL, Spark , and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with LLMs, LangChain, Agentic AI frameworks (e.g., AutoGen, CrewAI, BabyAGI) .
• Proficiency with Docker, Kubernetes, MLflow, Airflow, and GitHub .
• Familiarity with AWS services and observability tools like Grafana and CloudWatch.
• Exceptional communication, stakeholder management, and problem-solving skills.
• Proven leadership in cross-functional, innovation-focused environments.
• Domain Expertise:
• Strong understanding of supply chain systems (SAP, BY ESP, MES) and planning processes (MEIO, IBP, factory build planning).
• Why Join Us?
• Shape the future of Agentic and Generative AI-driven Supply Chain Transformation .
• Collaborate with global teams driving large-scale operational excellence.
• Work with cutting-edge AI tools to solve complex, real-world problems at enterprise scale.
• Sandisk thrives on the power and potential of div

Additional Information

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. ESSENTIAL DUTIES AND RESPONSIBILITIES: AI/ML, Generative AI & Agentic AI Development 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 insights across multiple enterprise systems (SAP, Blue Yonder, MES, Dynamics, etc.). Engineering & MLOps Build and maintain scalable AI/ML pipelines using Python , Pandas, Neural Prophet, SQL, Spark , and AWS tools (S3, Lambda, SageMaker). Utilize containerization (Docker) and orchestration (Kubernetes) for deployment of multi-agent applications. Apply MLOps best practices - CI/CD, model versioning, monitoring (Grafana, CloudWatch), and drift detection. Cross-Functional Collaboration Work with Planning, Procurement, Manufacturing, IT, and Engineering teams to identify and prioritize use cases for automation and decision augmentation. Present technical solutions, demonstrate prototypes, and communicate insights effectively to senior stakeholders. Innovation & Continuous Improvement Lead the exploration and adoption of Agentic AI frameworks for autonomous planning and execution in supply chain functions. Stay current with emerging technologies in AI/ML, GenAI, and distributed intelligence systems. Scale early-stage prototypes into enterprise-grade AI systems that deliver measurable operational efficiency. REQUIRED: Master's or PhD in Computer Science, Data Science, Statistics, or a related quantitative field with a focus on AI/ML. 5-7 years of experience in AI/ML model development and deployment, preferably in supply chain or manufacturing environments. Demonstrated success in designing and deploying LLM or agent-based systems for automation or optimization.

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