Senior data science engineer

• Job Type (exemption status):
  Exempt position - Please see related compensation & benefits details below
• Business Function:
  Data Science

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 Staff AI/ML Engineer to lead the design, development, and deployment of advanced AI/ML and Generative AI solutions that drive innovation across our engineering, manufacturing, and business operations.

This role requires deep expertise in machine learning engineering, data science methodologies, and large-scale AI systems
, combined with strong domain intuition in semiconductor/NAND environments
. You will operate at the intersection of data, models, and real-world systems
, translating complex, high-impact problems into scalable AI solutions.

Key Responsibilities

AI/ML, Data Science & Domain Integration

• Develop advanced machine learning, statistical, and optimization models to solve complex business and engineering problems
• Apply end-to-end data science rigor
  : problem framing, feature engineering, modeling, validation, and impact measurement
• Work with large-scale datasets (e.g., process, yield, test, operational data) to derive actionable insights
• Integrate domain knowledge (semiconductor/NAND processes, constraints, variability) directly into model design and interpretation
• Design and deploy GenAI solutions (LLMs, RAG pipelines, agent-based systems) for engineering and operational use cases
• Build knowledge-driven systems leveraging enterprise data (documents, logs, process data)
• Develop evaluation frameworks to ensure quality, grounding, and reliability of GenAI outputs
• Apply GenAI to enable decision support, automation, and productivity at scale

End-to-End System Architecture

• Architect production-grade AI/ML systems
  , including:
  • Data pipelines and feature engineering frameworks
  • Model training and experimentation platforms
  • Real-time and batch inference systems
• Design systems that balance accuracy, scalability, latency, and cost efficiency
• Establish patterns for integrating AI into existing enterprise platforms and workflows
• Build and scale MLOps pipelines (CI/CD, model registry, monitoring, drift detection)
• Ensure reproducibility, observability, and governance of AI systems
• Lead efforts to operationalize models into reliable, maintainable production systems
• Partner with cross-functional teams (engineering, manufacturing, product, IT) to translate requirements into solutions
• Mentor engineers and data scientists in advanced modeling, system design, and GenAI capabilities

Required

• Master’s degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related quantitative field
• 8–12+ years of experience in AI/ML engineering, data science, or related domains
• Strong expertise in:
  • Python and modern ML frameworks (PyTorch, Tensor Flow, scikit-learn)
  • Statistical modeling, experimentation, and data science methodologies
  • Scalable ML system design and production deployment
• Proven track record of delivering production-grade AI/ML systems with measurable business impact

Preferred

• PhD in a relevant field (e.g., Machine Learning,…