Applied ML Intern: Research & Recommender Systems

DoorDash USA; San Francisco, Sunnyvale, New York, Seattle (CA, CA, NY, WA); On-site; USD 131,000 - 285,000; Full time

Benefits offered by this job

Equity grants

401(k) with employer matching

16 weeks paid parental leave

Wellness benefits

Commuter benefits match

Paid time off & sick leave

Job summary

DoorDash is seeking a Machine Learning Engineer intern to join our fast-growing engineering team. You will work on challenges in ML/AI and conduct research applicable to multiple DoorDash teams, with mentoring and external collaborations.

The 12-week summer program will place you in San Francisco, Sunnyvale, New York, or Seattle offices. You’ll apply ML across discovery, ads, forecasting, and search, collect data insights, and build models.

Qualifications

• Pursuing PhD with expected graduation Fall 2027–Summer 2028.
• Strong mastery of at least one systems language or one ML framework.
• Experience in research and analytical problem solving.
• Strong communication and teamwork abilities.

Responsibilities

• Apply cutting-edge ML/AI research to real-world problems across discovery, ads, forecasting, fulfillment and search at DoorDash.
• Contribute and implement research ideas to improve product experiences.
• Collect and analyze data to build relevant ML models.

Skills

Java

C++

Python

Kotlin

GoLang

TensorFlow

PyTorch

MLFlow

Education

PhD in Computer Science, ML, NLP, Statistics, Information Sciences (or related)

Tools

Git

Job description

DoorDash is seeking a Machine Learning Engineer intern to join our fast-growing engineering team. You will work on challenges in ML/AI and conduct research applicable to multiple DoorDash teams, with mentoring and external collaborations.

The 12-week summer program will place you in San Francisco, Sunnyvale, New York, or Seattle offices. You’ll apply ML across discovery, ads, forecasting, and search, collect data insights, and build models.