Job Description

We are seeking a highly motivated GenAI & AI/ML Engineering Intern to join our Design Enablement & Automation (DE&A) team. This role offers an exciting opportunity to revolutionize Sandisk’s semiconductor development workflows through cutting-edge AI technologies.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Generative AI:

Develop and deploy large language models (LLMs) inference pipelines for electronic design automation
Design Retrieval-Augmented Generation (RAG) systems and semantic search capabilities for engineering documentation management
Implement conversational AI agents for technical support
Develop prompt engineering strategies and fine-tuning approaches for domain-specific AI assistants
Build multimodal AI systems combining text, code, and design diagrams
Implement model versioning, A/B testing, and performance monitoring for GenAI systems
Optimize GenAI model performance for production environments
Build evaluation frameworks for generative AI model quality and safety

AI/ML & Data Intelligence:

Develop machine learning models for design optimization and prediction
Build automated data pipelines and workflows for AI model training and inference
Create predictive analytics solutions using both traditional ML and generative approaches
Implement AI-driven anomaly detection and pattern recognition systems
Build dashboards and visualizations enhanced with natural language generation

Learning Opportunities:

Hands-on experience with state-of-the-art commercial and open-source generative AI models
Deep dive into RAG architectures, vector databases, and semantic search technologies
Exposure to enterprise-scale GenAI infrastructure and LLMOps practices
Experience with cutting-edge semiconductor design flows and tools enhanced by AI
Mentorship from senior engineers specializing in both GenAI and semiconductor design domains
Opportunity to contribute to GenAI development and present at AI/semiconductor conferences

Qualifications

Required:

Currently enrolled in a Bachelor's, Master's, or Ph.D. program in Computer Science, Electrical Engineering, Computer Engineering, Data Science, or related technical field
Strong programming skills in Python and experience with AI and data analytics frameworks (Spark, Ray, pandas, scikit-learn, PyTorch, OpenAI API, or similar)
Fundamental understanding of machine learning and generative AI concepts and algorithms
Experience with data structures, algorithms, and software engineering principles
Basic knowledge of natural language processing (NLP) and Generative AI concepts
Familiarity with version control systems (Git) and collaborative development workflows
Curiosity about applying AI to semiconductor design and engineering workflows
Ability to quickly learn new technologies and adapt to evolving AI landscape
Strong attention to detail and commitment to code quality and documentation

Preferred:

Hands-on experience with large language models (LLMs) and generative AI frameworks
Knowledge of Retrieval-Augmented Generation (RAG) systems and vector databases
Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes)
Familiarity with MLOps practices, model deployment, and monitoring tools
Understanding of prompt engineering and fine-tuning techniques for language models
Experience with data pipeline tools (Apache Airflow) and workflow orchestration
Knowledge of semiconductor design flows, electronic design automation (EDA), or hardware description languages (Verilog, VHDL)
Experience with web development frameworks and API design
Familiarity with database systems (SQL, NoSQL) and data visualization tools
Previous internship, research, or project experience in AI/ML or Generative AI applications