Staff AI/ML Engineer

We are seeking a Staff AI/ML Engineer in Data and AI team to drive the design, development, and operationalization of machine learning and GenAI solutions across Sandisks 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.
• Architect Agentic Harness and Design 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

Required Qualifications

• Masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• 9+ years of professional experience in AI/ML engineering, data science, or a related role, with demonstrated ownership of production ML systems and with at least 3+ years in AI/ML solution architecture or enterprise AI implementation.
• Deep expertise in machine learning algorithms, deep learning frameworks (PyTorch, TensorFlow), and statistical modeling.
• Expertise with vector databases, embedding models, and semantic search architectures.
• 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.
• 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).