Applied AI Research Scientist – Multi-Agent Systems

DoorDash High Volume; San Francisco (CA); On-site; USD 204,000 - 299,000; Full time

Job summary

DoorDash is seeking an applied AI researcher to work directly with our cofounder, owning the direction of AI research. You will develop agent environments and evaluation methods, design systems to improve agent performance, and curate data to enhance agent behavior at real-world scale.

This role is hands-on with immediate product impact in a fast-moving environment. You will collaborate with leadership, move quickly with high autonomy, and access global data and compute resources to drive AI

Qualifications

• 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 building infra for large-scale reinforcement learning and multi-agent reinforcement learning.
• Experience at frontier labs (OpenAI, Anthropic, DeepMind) or top AI startups.
• A builder mindset - you’re energized by experimentation, move quickly, and stay close to the work.
• Strong cross-functional instincts and a natural ability to bring research and product teams together.
• Nice to have: PhD with AI or other scientific domains.

Responsibilities

• Develop realistic agent environments and evaluation methods.
• Design systems and algorithms to improve agent performance.
• Collect and curate human and synthetic data to improve agent systems.

Skills

AI product development

Agent solutions

Reinforcement learning

Multi-agent RL

Cross-functional collaboration

Builder mindset

OpenAI/Anthropic/DeepMind experience

Education

PhD in AI or related

Tools

RL infra

Evaluation platforms

Context management

Job description

DoorDash is seeking an applied AI researcher to work directly with our cofounder, owning the direction of AI research. You will develop agent environments and evaluation methods, design systems to improve agent performance, and curate data to enhance agent behavior at real-world scale.

This role is hands-on with immediate product impact in a fast-moving environment. You will collaborate with leadership, move quickly with high autonomy, and access global data and compute resources to drive AI