PhD Fall Machine Learning Intern (ATG - Visual, Multimodal, and Recommender Systems)

About the role

This internship offers exposure to full-spectrum ML product development, focusing on visual understanding and recommender systems. Interns will conduct research, engage in collaborations, and potentially deploy features to millions of users.

Responsibilities

• Develop and launch new user features using ML techniques (recommendation systems, computer vision, generative AI, responsible AI).
• Gain hands-on experience with production ML systems.
• Leverage frontier AI tools to accelerate engineering.
• Validate AI-generated outputs.
• Use AI for code understanding and bug investigation.
• Contribute to cutting-edge ML/AI research.
• Write clean, efficient code.
• Take ownership of tasks with minimal guidance.

Qualifications

• Pursuing a PhD in Computer Science, ML, NLP, Statistics, or related field.
• Experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs.
• Proficiency in at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow).
• Proficiency with AI-native engineering and agent-friendly codebases.
• Strong critical thinking and problem-solving skills.
• Able to legally work full-time from September-December 2026.
• Strong communication and teamwork skills.

Preferred Qualifications

• Publications in machine learning, AI, data science, or related fields.
• Passion for research and applied ML.