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.
Key Responsibilities
- 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.
Required 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.
- Experience with cloud platforms (Azure preferred) and Lakehouse architectures (Databricks).
- Proven ability to translate business requirements into technical solutions and communicate results to non-technical stakeholders and senior leadership.
Preferred Qualifications
- Experience with Large Language Models (LLMs), prompt engineering, and GenAI application development.
- Familiarity with vector databases, embedding models, and semantic search architectures.
- Experience building agentic AI workflows and multi-LLM orchestration systems.
- Domain experience in semiconductor manufacturing, NAND Flash, or related hardware/electronics industries.
- Certifications in Cloud Architecture (Azure, AWS, or GCP).
Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.
Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [email protected] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.