Machine Learning Intern (Masters) - Summer 2027

About the Team

DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.

About the Role

As a Machine Learning Engineer intern at DoorDash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across DoorDash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices.

Responsibilities

• Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads, forecasting, fulfillment, and search experiences at DoorDash.
• Contribute and execute on research ideas that can be applied and used to improve product experience at DoorDash.
• Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models.
• Write clean, efficient, and sustainable code.

Qualifications

• Currently working towards a Master's degree in Computer Science, ML, NLP, Statistics, Information Sciences, or a related field, graduating between Fall 2027 & Summer 2028.
• Mastery of at least one systems language (Java, C++, Python, Kotlin, GoLang) or one ML framework (TensorFlow, PyTorch, MLflow).
• Experience in research and in solving analytical problems.
• Strong communicator and team player.
• Passion for applied ML and the DoorDash product.
• (Preferred) Experience working on publications in machine learning, AI, data science, data analytics, statistics, or related technical fields.