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Salary
$190k – $211k per year
Location
In office (New York)
Seniority
Senior · 7+ years exp
Overview
Company
Impact
Profile match
Uber Technologies, Inc. is a global transportation and mobility platform headquartered in San Francisco, California. Founded in 2009 by Garrett Camp and Travis Kalanick, the company revolutionized urban transit by pioneering ride-hailing via a smartphone app.

About the Role

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.

What the Candidate Will Do

You’ll tackle some of Uber’s most complex fulfillment problems, where software decisions meet the realities of grocery stores, couriers, and time-bound customer expectations. In this role, you will:

  • 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.

This role offers a rare opportunity to work simultaneously on logistics systems and optimization models, with direct influence on customer trust and business performance.

Basic Qualifications

  • 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.

Preferred Qualifications

  • 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.
~~ ~~

For New York City, NY-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD $190,000 per year - USD $211,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

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