Software Internship - AI & Battery Informatics at Sila… · Alameda

Summary: Sila Nanotechnologies, Inc. is a next-generation battery materials company focused on powering the world’s transition to clean energy. They are seeking an AI-forward software intern to bridge the gap between electrochemical R&D and production-grade data science, focusing on building autonomous workflows and data systems. Responsibilities: - Build and deploy autonomous AI agents to automate experimental management, enabling researchers to query, summarize, and reason over complex datasets - Develop automated pipelines for eg. SEM (Scanning Electron Microscopy) and other characterization techniques to automate feature extraction (e.g., particle morphology, particle sizing, feature extraction, and defect detection) - Data orchestration and optimization support for modeling teams with build and validate physics-based and ML- models (Transformers, GNNs) to predict battery performance - Design and optimize data pipelines capable of handling massive, high-frequency battery datasets (cycling, modeling) using advanced frameworks for out-of-memory processing - Support the development of backend pipelines, FastAPI tools, and internal dashboards (Hex, React,js) to bring AI-driven insights to a wider audience Required Qualifications: - BSc (or preferably MSc/currently enrolled in a Ph.D. program) in Computer Science, Materials Science, or a related field - Mastery of Python scientific libraries (NumPy, SciPy, Pandas) - Expert-level experience with high-performance frameworks like Polars, Vaex, or Dask for massive datasets - Experience building agentic workflows (e.g., LangGraph, CrewAI) and utilizing cloud-native AI functions such as Snowflake Cortex - Proficiency in OpenCV or deep learning-based image segmentation (e.g., SAM) for material characterization - Strong proficiency in building production-ready code, including K8s, Docker, and CI/CD pipelines - Basic understanding of Li-ion battery chemistry, materials processing, and electrochemical testing - Proficiency in using AI coding tools (e.g., Claude Code, Copilot) and Git-based collaboration Required Skills: Python, AI applications, Data pipelines Important Skills: OpenCV, Kubernetes, Docker, CI/CD pipelines Nice-to-Have Skills: Git, Cloud-native AI, Material characterization, Li-ion battery chemistry Benefits: Total Rewards package that can include benefits, perks, and equity.