Applied AI Engineering Intern at d-Matrix in Santa Clara, CA

Summary: d-Matrix is focused on unleashing the potential of generative AI to transform technology. As an Applied AI Engineering Intern, you will design and implement AI-powered solutions to improve manufacturing workflows, collaborating with cross-functional teams to enhance operational throughput. Responsibilities: - You’ll work at the intersection of LLMs and manufacturing—turning messy real-world data into systems that ship product faster and catch problems earlier - Build AI agents that diagnose why hardware tests fail—clustering failure signatures, surfacing probable root causes, and helping engineers skip weeks of manual triage - Design LLM-powered pipelines that ingest unstructured supplier and factory reports and turn them into structured, queryable data visible to the team in real time - Prototype intelligent document workflows that reconcile financial and procurement records, flagging discrepancies that today require hours of manual cross-checking - Benchmark multiple LLM backends (cloud and local) across your workloads to find the right cost–quality–latency trade-offs for production deployment - Collaborate with test, quality, and operations engineers to validate that what the models say actually matches what happens on the floor Required Qualifications: - Pursuing a Master's or PhD in Computer Science, Electrical Engineering, Industrial Engineering, or a related field - Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or scikit-learn) - Experience with data analysis and visualization (Pandas, NumPy, Matplotlib) - Familiarity with at least one of: time-series analysis, anomaly detection, optimization, or computer vision - Exposure to manufacturing, semiconductor, or hardware environments is a plus - Familiarity with version control (Git) and Linux-based development workflows Preferred Qualifications: - Prior internship or project experience in manufacturing analytics, digital twin, or process optimization - Experience with LLMs/generative AI for structured data or knowledge extraction - Exposure to statistical process control (SPC) or Six Sigma concepts Required Skills: Python, Machine Learning frameworks, PyTorch, TensorFlow, scikit-learn, Data analysis, Data visualization, Pandas, NumPy, Matplotlib, Time-series analysis, Anomaly detection, Optimization, Computer vision, Version control, Git, Linux development workflows, Manufacturing domain knowledge, Semiconductor domain knowledge, Hardware environment knowledge, Humility