Engineering Manager II, Ranking and Recommendations, Grocery and Retail

Uber

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
New York, NY
Posted
6 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $210k
$154k $264k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $167,450–$253,312.

Based on 240 similar postings.

Employer

About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

Uber currently has 107 open roles on FindRole.

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At a glance

TL;DR · Engineering Manager II, Ranking and Recommendations, Grocery and Retail

Engineering Manager II, Ranking and Recommendations, Grocery and Retail leads a team of backend and ML engineers responsible for the online ranking serving stack within the Grocery and Retail Consumer Ranking team. The manager oversees the evolution of online retrieval and ranking services, focusing on building high-throughput serving stacks that power seamless shopping experiences. Key responsibilities include managing the product roadmap, driving reliability for high-QPS services, and optimizing for p99 latency and resource costs. The role requires expertise in distributed systems, API design, and production serving. Candidates must integrate state-of-the-art models including Deep Learning, Embeddings, and GenAI into production environments. The work involves managing real-time and batch pipelines to ensure online and offline consistency for features and model inputs in a high-traffic retail context.

What does a Engineering Manager earn in New York?

Median $254488 from 41 postings across 13 companies.

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What you'll do

  • Lead a team of backend and ML engineers owning the online ranking serving stack.
  • Define and execute a multi-quarter product roadmap for ranking infrastructure and capacity planning.
  • Optimize p99 latency, tail-latency mitigation, and infrastructure cost efficiency for high-QPS services.
  • Oversee the development of real-time and batch pipelines to ensure online/offline data consistency.
  • Integrate Deep Learning, Embeddings, and GenAI models into a production environment at global scale.
  • Champion engineering culture through on-call health, post-mortems, and graceful degradation strategies.
  • Build and extend automated experimentation capabilities including guardrails, logging, and debiasing.

What we're looking for

  • 10+ years of experience in software engineering with a primary focus on high-traffic backend systems.
  • 4+ years of engineering management experience.
  • Deep experience in distributed systems, API/service design, and high-scale production serving.
  • Proven track record in managing SLOs/SLAs, incident response, and performance/latency optimization.
  • Experience delivering ML-backed services and partnering with DS/MLE on model requirements and evaluation.
  • Strong verbal and written communication skills with the ability to influence technical and product roadmaps.
  • Experience managing teams of 10+ engineers in a large-scale tech company (10k+ employees) (preferred).
  • Experience integrating with large-scale ML platforms and model rollout patterns (preferred).

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