GenAI & AI/ML Engineering Summer Intern

About the Role

Seeking a highly motivated GenAI & AI/ML Engineering Summer Intern to revolutionize Sandisk’s semiconductor development workflows through cutting-edge AI technologies.

Key Responsibilities

GenAI ESSENTIAL DUTIES AND RESPONSIBILITIES

• 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.

Requirements & Tech Stack

• 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.
• 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 Qualifications

• 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.