Associate Manager, AI Research Lab Strategy & Operations

DoorDash•San Francisco, CA

1d•Remote

About The Position

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. 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.

Requirements

Bachelor’s degree or higher
3+ years of experience in consulting, strategy, or operations; high-growth/early-stage startup or entrepreneurial experience is a big plus
Expert communication and interpersonal skills
Strong analytical thinker who can provide applicable recommendations out of a complex, sometimes murky, dataset
Bias towards action and are able to thrive in a fast-paced, constantly changing work environment
Charisma allows you to excel at connecting with Merchants and internal teams to promote products and drive adoption
Crave responsibility and want to shape the vision and direction of the company
Willing to get your hands dirty and you’re open to feedback.
Excellent at motivating potential partners to see the benefits DoorDash Commerce Platform will bring to their business
Must be comfortable regularly exercising discretion and independent judgment in performing job duties, including evaluating options, making informed decisions, and determining appropriate courses of action within the scope of assigned responsibilities.

Responsibilities

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 (e.g., AMPED, VAM, NBA, and other Mx-first efforts) 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 (e.g. OpenAI, Anthropic, and emerging startups), translating research breakthroughs into revenue-generating product capabilities and production systems.
Supporting the development of a DoorDash data collection marketplace, strengthening proprietary data advantages and long-term model performance.
Leading rapid experimentation cycles, validating product-market fit, measuring business impact, and ensuring AI initiatives translate into tangible outcomes.