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

Requirements

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

Benefits

Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdeep learningPythondata preprocessingfeature engineeringmodel trainingmodel evaluationmodel optimizationprompt engineeringMulti Agent Systems

Soft Skills

collaborationpresentationcommunication