Software Engineering Intern – AI Tools for Hardware Engineering

Our System Hardware Engineering Team builds and validates next-generation hardware systems. We are looking for an intern passionate about AI and software engineering to help us design and implement internal AI-powered tools that accelerate hardware design, testing, and analysis workflows.

This role offers a unique opportunity to work at the intersection of AI, software, and hardware engineering, learning how AI can transform engineering productivity at scale.

As an intern, you will:

• Design and prototype AI-driven tools that support hardware engineers in data analysis, test automation, and debugging workflows.
• Implement backend services in Python and frontend interfaces in TypeScript (React/Next.js).
• Integrate databases (SQL, vector databases) for data storage, search, and retrieval.
• Explore AI/ML workflows (embeddings, retrieval, summarization, code assistance).
• Collaborate with hardware and software engineers to translate requirements into working tools.
• Write clear documentation, tests, and deployment scripts.

Minimum Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, or related fields.
• Proficiency in Python with type hints and TypeScript (comfortable reading and writing code).
• Basic knowledge of web development (HTTP, REST APIs, frontend frameworks).
• Familiarity with databases (SQL queries, schema design).
• Strong problem-solving skills and curiosity to learn.
• Able to commit to a minimum 4 months full-time internship (preference for 6 months).
• Good written and spoken English communication skills.

Preferred Qualifications

• Experience with AI/ML frameworks (e.g., Hugging Face, LangChain, TensorFlow/PyTorch, or LLM APIs).
• Familiarity with at least one of FastAPI, Flask, Django or Node.js for web backend development.
• Hands-on knowledge of React/Next.js for web frontend development.
• Experience with PostgreSQL, Redis, or vector databases (e.g., Qdrant, Pinecone, FAISS).
• Interest in system hardware engineering workflows (test automation, data analysis, hardware validation).
• Enthusiastic, self-driven, and comfortable working in a collaborative engineering environment.