Member of Technical Staff, Applied AI Research

Experience with the latest AI tools building AI products

Familiarity with building agent solutions, including context management, defining evals, measuring performance

Strong knowledge of reinforcement learning techniques

Experience at frontier labs (OpenAI, Anthropic, DeepMind) or top AI startups.

Nice to have: PhD with AI or other scientific domains

You have 10+ years of experience designing and scaling distributed data systems, with deep expertise in NoSQL technologies like Apache Cassandra, DynamoDB, or ScyllaDB.

You'll work directly with our cofounder with direct ownership over the direction of AI research at DoorDash.

In this role you will develop realistic agent environments and evaluation methods, design systems and algorithms to improve agent performance, and collect and curate human and synthetic data to improve the capability and behavior of agent systems.

This is hands-on work with immediate product impact at real-world scale.

Work directly with leadership and see your research deployed at real-world scale - small team, massive reach.

Have access to global data scale, robust compute, and a platform primed for AI transformation.

Shape how AI transforms commerce, building intelligent and adaptive experiences for millions of Consumers, Merchants, and Dashers.

The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers.