PhD Machine Learning Internship 2027 (USA)
About this role
Researchers who thrive on solving open-ended problems and want to shape large-scale recommendation systems will find a strong fit in this program. Pinterest is hiring PhD machine learning interns to help build personalized features for millions of users worldwide through hands-on research and production ML systems.
During the twelve-week term, interns lead an independent project from start to finish. Participants tackle challenges across image recognition, user modeling, search, ads, ranking, natural language processing, and graph representation learning. Mentors and managers guide the process while encouraging autonomous problem-solving and collaboration across engineering teams.
Candidates pursuing a doctorate in computer science or related technical fields who enjoy applying algorithmic research to real-world products do well here. The internship offers fixed start dates in May or June and provides monthly compensation of $12,100.
What you will do
- Lead an independent project from start to finish to contribute to machine learning and artificial intelligence research applicable to Pinterest problems.
- Gain hands-on experience with production ML systems encompassing algorithmic research, infrastructure, data engineering, training, inference, and product delivery.
- Leverage frontier AI tools and agents to accelerate engineering implementation, prototyping, and experimentation work.
- Validate AI-generated outputs through testing, code review, and critical thinking to ensure accuracy, maintainability, security, and alignment with team standards.
- Utilize AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation.
- Write clean, efficient, and sustainable code while taking proactive ownership over task completion and project quality.
What you need
- Must be currently working towards a PhD in Computer Science, Machine Learning, Natural Language Processing, Statistics, Information Sciences, or a related field.
- Demonstrate proficiency in at least one systems language such as Java, C++, or Python, or an ML framework like TensorFlow, PyTorch, or MLFlow.
- Show proficiency with AI-native engineering, including the design of agent-friendly codebases and autonomy in learning new agent-first development tools.
- Apply strong critical thinking when working with AI-generated suggestions, maintaining a clear approach to validating correctness, performance, security, and maintainability.
- Possess prior experience in research and in solving analytical problems.
- Demonstrate strong communication skills, teamwork, and the ability to find solutions for open-ended problems.
Nice to have
- Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields.
- Interest in research and in applying machine learning to impactful real-world problems on the Pinterest product.
Benefits
- 12 weeks paid internship with fixed start dates in May or June
- Mentorship from experienced engineers and researchers
- Participation in professional development workshops and networking events
Skills and tech stack
Questions candidates ask
Where is the internship located and what is the remote policy?
Depending on the team, summer internships will be located either remote or hybrid in San Francisco, Palo Alto, New York, or Seattle offices. The role may require you to be located near an office for in-person collaboration.
What is the pay for this position?
The salary for this position is $12,100 monthly. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
How long does the internship last and when does it start?
Internships are 12 weeks paid, with fixed start dates in May or June to accommodate varying school calendars. The two available start dates are May 17, 2027 to August 6, 2027 and June 14, 2027 to September 3, 2027.
What qualifications are required to apply?
Candidates must be working towards a PhD in Computer Science, ML, NLP, Statistics, Information Sciences, or a related field. Applicants also need proficiency in at least one systems language or ML framework and experience in research.