PhD Fall Machine Learning Intern (ATG — Visual, Multimodal, and Recommender Systems)
PhD intern in Pinterest's Advanced Technology Group develops ML features for visual understanding and recommender systems, conducts cutting-edge research, and deploys to production. Requires PhD candidacy in CS/ML-related field, proficiency in systems languages and ML frameworks, and AI-native engineering skills.
145k – 145k/yr
HybridML Engineering
About the role
What you’ll do
Develop and launch new user features using unique internal datasets and ML techniques, especially in recommendation systems, computer vision, representation learning, generative AI, and responsible AI.
Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems.
Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work.
Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards.
Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
Write clean, efficient, and sustainable code
Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers
What we’re looking for
This role will be on our Visual Search or Applied Science teams. We are looking for candidates with experience in Computer Vision, Visual Search, User Understanding, Recommendation Systems, Reinforcement Learning, ML efficiency optimization, Generative AI, and LLMs.
Ability to legally work full time (40 hours/week) from September-December 2026
Working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
Proficiency with AI-native engineering, including the design of agent-friendly codebases.
High degree of autonomy in learning new agent-first development tools.
Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
Experience in research and in solving analytical problems
Strong communicator and team player. Being able to find solutions for open-ended problems.
Preferred Qualifications
Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
Strong passion for research and for answering hard questions with research
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