Senior Engineer, Data Management Engineering

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 looking for a curious and motivated Junior Data Management Engineer with foundational experience in machine learning, Computer Vision and GenAI to join our growing data team. This role is perfect for someone early in their career who is eager to contribute to data engineering tasks while gaining hands-on exposure to machine learning workflows. You'll help ensure data pipelines are optimized for analytics and ML model development, supporting both operational and strategic decision-making.

Responsibilities

Work with multiple stakeholders to identify, diagnose and resolve manufacturing process related problems such as quality excursions, manufacturing excellence and cost improvement.; Apply computer vision algorithms to inspect production lines for defects, improve yield, and enhance overall quality control. Leverage techniques such as object detection, image segmentation, and defect localization to identify issues early in the manufacturing process.; Build, train, and validate machine learning models to address complex manufacturing challenges, such as defect detection, process optimization, and performance prediction.; Able to deploy trained models into production environments, including APIs, edge devices, or embedded systems. Ensure seamless integration with manufacturing systems and establish real-time monitoring for model performance.; Design and develop scalable GenAI applications using LLMs tailored to manufacturing use cases.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.; 0–2 years of experience in data analytics, data engineering, or machine learning.; Proficiency in SQL for data querying and manipulation.; Strong programming skills in Python, experience with SQL, Spark, or other big data tools for processing large-scale manufacturing/sensor datasets.; Proficiency in ML frameworks (PyTorch, TensorFlow/Keras) and CV libraries (OpenCV, Detectron2, MMDetection).; Experience with model deployment in production (eg, Docker, Kubernetes, edge devices) for real-time or batch inference.; Data preprocessing and feature engineering techniques.; Ability to interpret and visualize data insights.; Strong analytical and problem-solving mindset.; Effective written and verbal communication.; Team collaboration and a proactive learning attitude.

Nice to have

Exposure to building or assisting in ML models using libraries like scikit-learn or TensorFlow.; Experience with data visualization tools (e.g., Spotfire, Power BI, Tableau).; Familiarity with version control tools such as Git.; Exposure to ML lifecycle tools like MLflow, DVC, or Kubeflow.