AI Research Fellowship, (Summer and Fall 2026)

What you'll do

• Define and scope a research agenda within priority areas like reinforcement learning or multimodal understanding.
• Develop high-fidelity simulators using real-world operational data for training AI models in logistics and local commerce.
• Conduct independent research with access to DoorDash’s advanced infrastructure, including GPU clusters and internal RL stack.
• Publish findings at top ML venues such as NeurIPS, ICML, ICLR, or KDD under the fellowship's publication support program.
• Collaborate with a cohort of fellows for shared ideas, drafts, and reading groups while receiving mentorship from senior researchers.

What we're looking for

• PhD candidates or recent PhDs with a strong track record in ML research.
• Experience operating independently to set, scope, and execute a research agenda.
• Deep understanding of reinforcement learning environments for real-world operations.
• Strong written and verbal communication skills for mixed audiences.
• Published work at top ML venues like NeurIPS, ICML, ICLR, or equivalent output.
• Interest in foundation models for marketplace dynamics, including forecasting and matching.