Machine Learning Intern (Masters) - Summer 2027

DoorDash · 348 University Recruiting Engineering

Pay: $130,600–$285,000/hr
Where: San Francisco, CA; Sunnyvale, CA ; New York City, NY; Seattle, WA
Posted: Sep 24

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.

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.

What you'd do

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

What they want

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
For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).