[Sept 2026 Intake - Fresh Grad Only] Senior/Engineer, Data Analytics 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.

Responsibilities

Assist in the design and development of NLP pipelines for tasks like entity recognition, summarization, sentiment analysis, and question answering.; Preprocess and clean text data for training and evaluation of LLMs.; Experiment with state-of-the-art LLM frameworks (e.g., Hugging Face Transformers, OpenAI API, LangChain) to solve real-world text processing problems.; Support fine-tuning of pre-trained models on domain-specific datasets using techniques like LoRA, PEFT, or full model training.; Develop and maintain prompt engineering strategies for improving model performance.; Research and implement techniques for RAG (Retrieval-Augmented Generation) and context optimization.; Document experiments and present findings to the team.

Requirements

Bachelor's/master’s degree in computer science/Engineering, data science or related field.; Experience in programming language (python, R) and database (SQL) to perform data mining and analysis.

Nice to have

Knowledge of statistical techniques in data science (regression, properties of distribution).; Knowledge in machine learning techniques (neural network, machine learning).; Strong analytic skills and problem-solving skills.