Overview

Company Description

Responsibilities

• 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 Senior AI/ML Engineer in Data and AI team to drive the design, development, and operationalization of machine learning and GenAI solutions across Sandisk's enterprise. In this role, you will own end-to-end AI/ML projects, from problem framing and data strategy through model deployment and monitoring. You will partner directly with business stakeholders to translate complex requirements into scalable, production-grade solutions and mentor junior engineers on the team.
• Lead the end-to-end design, development, and deployment of machine learning models and GenAI solutions for manufacturing intelligence, yield optimization, supply chain analytics, and enterprise data platforms.
• Architect and implement data pipelines, feature stores, and model serving infrastructure on Lakehouse and cloud-native architectures (Databricks, Azure).
• Develop prompt engineering strategies and feedback loops for LLM optimization; capture and normalize LLM interactions into reusable Knowledge Artifacts.
• Implement Retrieval-Augmented Generation (RAG) pipelines, including document parsing, chunking, vectorization, and semantic search using embeddings and vector databases. Support domain-specific ontologies, taxonomies governance and versioning.
• Design agentic workflows using industry-standard frameworks for autonomous task orchestration and multi-step reasoning, with safe and controlled execution via constraints, policies, and fallback paths.
• Collaborate with cross-functional teams to define KPIs, success metrics, and business impact measurements for AI/ML initiatives.
• Mentor intermediate and junior engineers; conduct code reviews and establish best practices for ML engineering.
• Present technical findings and strategic recommendations to senior leadership, distilling complex results into actionable business insights.

Qualifications

• Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of professional experience in AI/ML engineering, data science, or a related role, with demonstrated ownership of production ML systems.
• Deep expertise in machine learning algorithms, deep learning frameworks (PyTorch, TensorFlow), and statistical modeling.
• Strong proficiency in Python; experience with distributed computing frameworks (Apache Spark) and SQL.
• Hands-on experience with MLOps practices: model versioning (MLflow), CI/CD for ML, automated retraining, monitoring, and drift detection.
• Proven ability to translate business requirements into technical solutions and communicate results to non-technical stakeholders and senior leadership.
• Familiarity with vector databases, embedding models, and semantic search architectures.
• Domain experience in semiconductor manufacturing, NAND Flash, or related hardware/electronics industries.
• Certifications in Cloud Architecture (Azure, AWS, or GCP).