Machine Learning Intern (PhD) - Summer 2027
About this role
Researchers pursuing a PhD who enjoy applying theoretical concepts to massive datasets will thrive in this environment. DoorDash maintains a fast-growing engineering team focused on building a 24x7 global infrastructure system to support a three-sided marketplace for consumers, merchants, and dashers.
Interns tackle complex challenges in artificial intelligence by conducting research that applies directly to company engineering teams. Participants also engage in external collaborations, mentoring, and specialized focus areas like auction design, game theory, recommender systems, and computer vision during the 12-week summer program.
What you will do
- Utilize advanced research methodologies in machine learning, natural language processing, recommender systems, ranking, computer vision, causal inference, ad tech, and graph analysis to address real-world problems.
- Contribute and execute research ideas designed to improve product experiences across discovery, ads, forecasting, fulfillment, and search.
- Collect, analyze, and synthesize data findings to build relevant machine learning models.
- Write clean, efficient, and sustainable code for production environments.
- Participate in external collaborations and mentoring activities during the program.
What you need
- Currently working towards a PhD degree in Computer Science, Machine Learning, Natural Language Processing, Statistics, Information Sciences, or a related field.
- Graduating between Fall 2027 and Summer 2028.
- Demonstrate mastery of at least one systems language such as Java, C++, Python, Kotlin, or GoLang, or familiarity with machine learning frameworks like Tensorflow, Pytorch, or MLFlow.
- Possess proven experience in research and solving complex analytical problems.
- Act as a strong communicator and team player who is passionate about applied machine learning.
Nice to have
- Prior publications in machine learning, artificial intelligence, data science, data analytics, statistics, or related technical fields
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- Medical, dental, and vision benefits
- Flexible paid time off plus 80 hours of paid sick time per year
- Disability and basic life insurance
- Wellness and commuter benefits
Skills and tech stack
Questions candidates ask
What is the duration and location of the internship?
The program runs for 12 weeks during the summer. Interns work out of the San Francisco, Sunnyvale, New York, or Seattle offices.
What is the compensation for this role?
The starting base pay falls within a range of $130,600 to $192,000 USD, determined by factors such as skills, experience, qualifications, and work location. In addition to base salary, the compensation includes opportunities for equity grants.
What qualifications do I need to apply?
Applicants must be working towards a PhD degree in Computer Science, Machine Learning, Natural Language Processing, Statistics, Information Sciences, or a related field with graduation dates between Fall 2027 and Summer 2028. Candidates also need mastery of at least one systems language or machine learning framework along with research experience.