- Job type
- Internship
- Work mode
- On-site
- Level
- Intern
- Department
- Engineering
- Experience
- Not listed
- Posted
- Sep 24, 2026
About the role
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.
You’re excited about this opportunity because you will…
- 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
We’re excited about you because you…
- Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028
- Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow)
- Have experience in research and in solving analytical problems
- Are a strong communicator and team player.
- Have a passion for applied ML and the Doordash product
- Ideally have worked on publications in machine learning, AI, data science, data analytics, statistics, or related technical fields