Engineering Intern (AI/ML & Automation) for Hardware

Just be ready to dream big.

The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that encourages the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.

Imaging what you could do here. At Apple, creative ideas have a way of becoming wonderful products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.

Description Our Product Safety Engineering Team is looking for a talented and enthusiastic Engineering Intern (AI/ML & Automation) to help develop cutting-edge AI-driven tools, data analysis platforms, and lab automation software. In this role, you will work at the intersection of AI/ML, full-stack software development, and hardware safety validation—building intelligent solutions that accelerate test data processing, safety compliance analysis, risk assessment, and test automation workflows.

Minimum qualifications • Currently pursuing a Master’s degree or PhD in Computer Science, Software Engineering, Electrical/Electronic Engineering, Mechanical/Automation Engineering, or a related technical field. • Able to commit to a minimum 6 months full-time internship in Shanghai. • Strong programming proficiency in Python etc. • Solid understanding of web application development (HTTP, RESTful APIs, modern frontend/backend architecture). • Familiarity with database fundamentals (SQL queries, data schema design). • Strong analytical, problem-solving, and debugging skills. • Good written and spoken communication skills in both English and Mandarin Chinese.

Preferred qualifications • Experience with AI/ML frameworks and libraries (e.g., PyTorch, Hugging Face, LangChain, LlamaIndex, or LLM API integrations). • Hands-on web development experience using FastAPI / Flask and React / Next.js. • Knowledge of vector databases (e.g., Qdrant, Pinecone, FAISS) and embedding/retrieval (RAG) pipelines. • Experience or interest in hardware test automation, lab instrumentation, sensor data acquisition, or safety/reliability testing workflows. • Familiarity with containerization (Docker), Git version control, and Linux environments. • Proactive, curious, self-driven, and comfortable collaborating in a fast-paced engineering team.