Associate Manager, AI Research Lab Strategy & Operations

About the Team

AI Research Lab is one of DoorDash’s frontier innovation hubs, focused on building the foundation for an AI-native future across our three core audiences: consumers, merchants, and dashers. As AI capabilities accelerate, the AI Research Lab operates at the center of technical exploration and real-world execution — connecting frontier model research, internal platform investments, operator teams, and strategic external partners.

Our mission is to translate cutting-edge AI research into scalable, production-ready systems that drive measurable business impact. We combine deep technical rigor with strong operational execution to ensure that breakthrough capabilities become durable competitive advantages for DoorDash.

About the Role

As an Associate Manager, Strategy & Operations on our AI Research Lab, you will play a central role in converting frontier AI advancements into shipped products and scalable infrastructure. You will operate across research, product, and operations to move from early discovery and experimentation to deployment and impact.

This role sits at the intersection of customer insight, technical innovation, and business execution. You will help define and scale the Lab’s most important bets while building the foundations that enable AI applications to compound over time.

You’re Excited About This Opportunity Because You Will …

• Reimagining core experiences through AI, such as the merchant journey, by partnering directly with in-field merchants, sales, support, product, and engineering teams. You will help unify major initiatives into a coherent, AI-native interaction model.
• Own revenue-driving AI initiatives, operating as the accountable business owner for high-priority AI bets and ensuring clear linkage between technical progress and financial outcomes.
• Lead business planning cycles, developing go-to-market strategies for AI-powered products and capabilities, overseeing execution through structured project plans, resource allocation, and KPI tracking.
• Develop new business metrics and measurement frameworks, including:
• Defining what should be measured and why
• Establishing performance thresholds using data-driven benchmarking
• Localizing metrics across geographies and market types
• Driving AI adoption across DoorDash by enabling non-technical teams with enterprise tools, workflows, and experimentation sandboxes that integrate AI into daily operations.
• Building scalable AI foundations, including evaluation datasets, guardrails, monitoring systems, and strategies for custom foundation models that ensure safety, reliability, and long-term leverage.
• Operationalizing frontier technologies from external partners, translating research breakthroughs into revenue-generating product capabilities and production systems.
• Leading rapid experimentation cycles, validating product-market fit, measuring business impact, and ensuring AI initiatives translate into tangible outcomes.

This role requires an entrepreneurial leader who thrives in ambiguity and can bridge technical depth with structured execution. You should be comfortable engaging directly with merchants, collaborating with engineers on model evaluation strategies, structuring strategic AI partnerships, and diving into metrics to diagnose performance. 

We’re excited about you because…

• Bachelor's degree and 5+ years of experience in finance, management consulting, business operations, business analytics, or high-growth/early-stage startup environments
• Exceptional communicator and operator who can partner directly with in-field merchants, sales, and support teams to uncover workflow pain points, translate them into AI-native product opportunities, and drive adoption across internal stakeholders                                                                                                                                                                             
• Strong analytical thinker who thrives in ambiguity and 0-to-1 environments — able to extract clear, actionable recommendations and measurement frameworks out of fast-moving, frontier-AI research and bring structure to unstructured problems                                                                                                                                                                                         
• Hands-on experience leveraging AI tooling (Claude Codex, Codex, Cursor etc) in day-to-day work to accelerate discovery, prototype workflows, build eval datasets, and test hypotheses faster than traditional product cycles allow
• Direct experience productizing LLM/ML systems (shipping features, building eval datasets, or running model-performance feedback loops) is a strong plus