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About Altera

At Altera™, our independence as the world’s largest pure‑play FPGA solutions provider gives us the focus, speed, and agility to innovate without compromise. With more than four decades of industry‑leading FPGA expertise, our singular mission is to deliver the programmable technologies that help customers differentiate, innovate, and scale across rapidly evolving markets like AI, cloud, networking, and edge. As an independent company, we move faster, invest deeper, and partner more closely—empowering our teams to drive breakthrough innovation and shape the future of the FPGA industry.

About the Role

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.

Key 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 We Value

• Engineering excellence and continuous improvement mindset.

• Passion for automation and applying AI to real-world engineering problems.

• Initiative to observe, learn, and propose impactful solutions.

• Ability to execute in a lean, collaborative environment.

Qualifications:

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

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