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Uber Grocery & Retail is scaling into a daily-use, trust-based delivery platform. Fulfillment Optimization is at the center of that ambition. As Senior Product Manager, Grocery Fulfillment Optimization, you will own the systems and decision logic that determine last-mile order fulfillment and how reliably, efficiently, and cost-effectively it happens when conditions are imperfect. This role sits at the intersection of marketplace algorithms, real-world logistics, and customer trust. You will work deeply with Marketplace and Data Science to design matching, batching, and recovery systems that adapt dynamically to supply, demand, store readiness, and inevitable failure modes, without degrading the customer or earner experience. The work spans both physical-world execution (stores, couriers, timing, constraints) and abstract optimization (matching, batching, objective functions, cost-per-trip). The outcome directly impacts reliability, unit economics, and long-term platform credibility. This is a senior IC role. We expect you to own ambiguous, cross-cutting problem spaces end-to-end, set direction for modeling and experimentation across teams, and influence roadmaps and prioritization well beyond your immediate scope.
Job Responsibility
Own the decision logic behind grocery fulfillment: how orders are matched, batched, planned, recovered, and completed when real-world conditions change
Partner closely with Marketplace and Data Science to define matching, batching, and assignment logic that balances reliability, cost-per-trip, earner experience, and store readiness, making tradeoffs explicit and testable in code, not debated in meetings
Design resilient fulfillment systems that treat recovery and graceful degradation as core product surfaces. Build backup fulfillment paths, partial-fulfillment recovery, and risk-based reassignment that materially reduce cancellations, missed deliveries, and partial fulfillment
Translate operational complexity into product and modeling requirements, ensuring systems behave predictably across edge cases, degraded states, and at scale
Shift fulfillment from reactive to proactive — build systems that anticipate risk (scheduled orders, supply variability, store performance) and adapt before customers feel the impact
Set direction for modeling and experimentation, influencing the roadmaps of partner teams (Matching, Pricing & Incentives, Ops Tech) to move the system as a whole
Requirements
7+ years of product management experience delivering successful, durable products, with clear ownership and outcomes you can point to. Your fingerprints are all over what shipped, what scaled, and what materially improved the business
Strong technical and operational fluency. You've built complex systems directly or worked close enough to real-world operations — last mile supply chain and logistics networks — to understand how theory breaks in practice. You can reason comfortably from high-level system design (distributed systems, event-driven architectures, APIs) down to edge cases, data flows, and how software behaves under real operational constraints and failure modes
Experience building algorithmic or ML-adjacent products in close partnership with Data Science. You understand how objective functions, constraints, experimentation, and model tradeoffs translate into real marketplace and fulfillment outcomes
Hands-on data fluency. You get the data you need on your own — SQL, dashboards, instrumentation — and turn it into insight that drives decisions, not analysis paralysis
Exceptional attention to detail. You obsess over how systems behave in the real world across customers, earners, merchants, and operations, and you notice the gaps, edge cases, and failure modes others miss
Customer obsession. You take on messy, high-stakes problems and find elegant, simple solutions so customers and partners don't have to carry platform complexity
A strong "driver" mindset. You are biased toward action, a great collaborator, a master disambiguator and simplifier, and relentless about pushing work to clarity and delivery
Sound judgment under ambiguity. You can reason through multi-sided tradeoffs — reliability, cost, customer experience, earner experience, and merchant outcomes — and make principled decisions with imperfect information
Influence without authority. You move multiple teams in the same direction by setting clear strategy, raising the bar on quality, and earning trust through judgment and execution
A consistently high bar. For your own contributions and for the products you ship
A never-ending desire to learn and grow. You seek feedback, adapt quickly, and continuously sharpen your craft
Nice to have
Direct grocery, last-mile, or supply chain fulfillment experience at scale. Dispatch, matching, routing, picking, or sortation systems in production, ideally with both system ownership and operations-side exposure
Ownership of decision systems, not just diagnostic or detection tooling, the logic that decides what the system actually does when the plan breaks
Experience launching products side-by-side with Data Science on optimization models: co-designing objective functions, constraints, and experimentation strategy
Experience building products from 0→1 in ambiguous problem spaces, especially in marketplaces or multi-sided platforms
Experience in grocery, retail, CPG, or e-commerce, especially where physical-world execution and software optimization intersect