AI / Machine Learning Intern at Calix in Remote

Summary: Calix is looking for a Summer intern to join our Products organization. In this role, you will work on real-world AI/ML and Generative AI problems, contributing to models, pipelines, and intelligent systems that power next generation Calix products. Responsibilities: - Design, implement, and experiment with machine learning and deep learning models for product use cases - Work on end‑to‑end ML workflows, including: - Data preprocessing and feature engineering - Model training, evaluation, and optimization - Experiment tracking and result analysis - Contribute to Generative AI and agentic systems, including: - LLM‑based workflows - AI agents, orchestration, and prompt engineering - Develop prototypes and proof‑of‑concepts that can evolve into production features - Write clean, maintainable, and well‑documented Python code - Collaborate with cross‑functional teams (engineering, product, platform) - Present findings, demos, and outcomes to the broader team Required Qualifications: - Currently enrolled in a college degree program in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related engineering discipline. Preference will be given to those who have at least completed their Junior year and have previous internship or work experience - Strong Python programming skills - Solid understanding of core AI / ML concepts, including Multi Agent Systems, MCP server and tool calling, supervised and unsupervised learning, model evaluation and validation, feature engineering basics - Familiarity with common AI / ML libraries / frameworks such as LangGraph, CrewAI, Google ADK, Microsoft AutoGen, PyTorch, TensorFlow, or scikit-learn - Comfortable working in a Linux/Unix environment - Experience using Git or other version control systems Preferred Qualifications: - Hands‑on project experience in Machine Learning / Deep Learning, Generative AI or LLM‑based systems, and Agentic AI or multi‑agent frameworks - Exposure to NLP, time‑series, recommendation systems, or anomaly detection and model deployment concepts or MLOps fundamentals - Experience with Cloud platforms (AWS, GCP, or Azure) and data processing frameworks (e.g. Spark) - Strong problem‑solving mindset and curiosity to explore new AI techniques - Able to work for the complete summer break (May - August or June - September) Required Skills: Python programming, AI / Machine Learning concepts, Multi Agent Systems, MCP server, tool calling, Supervised learning, Unsupervised learning, Model evaluation, validation, Feature engineering, AI / ML libraries, frameworks, LangGraph, CrewAI, Google ADK, Microsoft AutoGen, PyTorch, TensorFlow, scikit-learn, Linux/Unix environment, Git, version control systems