GenAI / Machine Learning Intern – Design Automation (AI Agents)

Altera • San Jose, CA

2d • $80,000 - $90,000

About The Position

Altera is seeking a passionate and driven GenAI / Machine Learning Intern - Design Automation (AI Agents) to join our Design Automation team. You must be actively enrolled in school and pursuing a Bachelor's degree in the required fields to be eligible for this internship. This role is ideal for someone who thrives at the intersection of data engineering, machine learning, process automation, and agentic AI. You will help build end‑to-end GenAI systems that leverage both structured and unstructured engineering data to streamline workflows and enhance productivity across engineering teams.

Requirements

• Must be currently pursuing a Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related field.
• 3+ months of experience or coursework with data engineering concepts, including ETL, data wrangling, and data integration; familiarity working with SQL, CSV, logs, text, and XML data formats.
• 3+ months of experience or coursework in Python programming and working with machine learning frameworks such as PyTorch or TensorFlow.

Nice To Haves

• 3+ months of experience or exposure to AI agent frameworks and tools (e.g., LangChain/LangGraph, Semantic Kernel, Hugging Face agents, OpenAI function calling patterns) and retrieval-augmented generation (RAG) concepts, including vector search, embeddings, chunking, and evaluation.
• 3+ months of experience applying agent reliability concepts, including prompt and tool design, grounding, guardrails, evaluation, and monitoring.
• 3+ months of experience demonstrating strong analytical and problem-solving skills with an engineering mindset.
• 3+ months of experience collaborating in team environments, with strong written and verbal communication skills.

Responsibilities

• Design and implement GenAI/ML pipelines to support physical design workflows.
• Develop ETL processes to extract, transform, validate, and join data from diverse sources (structured + unstructured).
• Create AI agents that can reason over engineering context and take actions across tools/workflows (e.g., triage logs, summarize run results, propose fixes, generate reports, automate repetitive flows).
• Implement agent tool-use patterns (retrieval, function calling, workflow orchestration) with guardrails and observability.
• Automate repetitive engineering tasks by observing workflows and identifying optimization opportunities.
• Collaborate with cross‑functional teams (design, verification, software) to understand data needs and integration points.
• Build and test prototypes/tools that demonstrate measurable value (cycle-time reduction, fewer manual steps, improved signal-to-noise).
• Document processes, evaluation methods, and best practices; contribute to knowledge sharing across teams.

What This Job Offers

• Career Level: Intern