What are the responsibilities and job description for the Senior Engineering Manager - Membership position at Uber?
About The Role
Uber One is Uber's powerhouse growth engine, commanding a global footprint of 45M members across 40 countries . At the heart of this success is the Membership Growth team-the architects of our member-first ecosystem. We are responsible for the end-to-end lifecycle of our most valuable users, driving sustained growth by engineering high-velocity solutions for acquisition, retention, and intelligent incentive optimization.
As a Senior Engineering Manager, you will lead a high-stakes organization of 20 engineers and one reporting Engineering Manager. This role sits at the critical intersection of Product Engineering and Machine Learning. You will move the needle on global growth by building the next generation of Personalized Upsell and Retention Engines-moving from static rules to dynamic, model-driven experiences that deliver value to users at the exact moment of intent.
What You Will Do
Uber One is Uber's powerhouse growth engine, commanding a global footprint of 45M members across 40 countries . At the heart of this success is the Membership Growth team-the architects of our member-first ecosystem. We are responsible for the end-to-end lifecycle of our most valuable users, driving sustained growth by engineering high-velocity solutions for acquisition, retention, and intelligent incentive optimization.
As a Senior Engineering Manager, you will lead a high-stakes organization of 20 engineers and one reporting Engineering Manager. This role sits at the critical intersection of Product Engineering and Machine Learning. You will move the needle on global growth by building the next generation of Personalized Upsell and Retention Engines-moving from static rules to dynamic, model-driven experiences that deliver value to users at the exact moment of intent.
What You Will Do
- Organization Leadership: Lead and scale a multidisciplinary organization of 20 engineers (Backend, Mobile, MLE and Web) and one reporting Engineering Manager.
- Personalization & Upsell Strategy: Architect systems that leverage real-time intent signals and propensity models to deliver personalized upsells across Uber and UberEats, ensuring we maximize conversion without cannibalizing organic growth.
- Drive "Big Bets": Formulate and execute the strategy for high-impact growth initiatives, such as global incentive targeting, multi-armed bandit experimentation frameworks, and intelligent churn prevention.
- MLE & Product Synergy: Lead a team of Machine Learning Engineers (MLEs) to translate business objectives into algorithmic formulations, bridging the gap between complex ML models and seamless user-facing product features.
- Vision & Roadmap: Partner with Product, Data Science, and Ops to define a compelling vision for growth that balances high-velocity experimentation with long-term platform stability.
- Hiring & Talent Development: Own the talent strategy for your group, including hiring top-tier talent and the professional development of your reporting Engineering Manager.
- Analytical Mindset & Experimentation: Proven ability to navigate A/B testing, data-driven decision-making, and ambiguous business problems. You must be comfortable defining success metrics and iterating based on data.
- Communication & Stakeholder Management: Exceptional communication skills with the ability to distill complex technical concepts for non-technical stakeholders and represent a large engineering group in global business discussions.
- Execution Excellence : Proven track record of delivering complex, cross-team projects with company-wide impact on time and with high quality.
- Education : Bachelors (or higher) in Computer Science, Engineering, or a related field.
- Management Track Record : 6 years of experience managing engineering teams, with specific experience managing other Engineering Managers and large-scale organizations (20 people).
- Technical Industry Experience : 12 years of software engineering experience, with a deep understanding of distributed systems and scalable backend architecture.
- Growth Domain Expertise : Deep experience in the Growth space, specifically in Acquisition, Retention, and LTV (Lifetime Value) optimization.
- Leading Machine Learning Teams : Proven experience leading MLEs and a strong intuition for applying ML to product optimization and personalization at scale.
- Incentive Optimization : Experience building or leading teams that build "Personalization at Scale," utilizing ML for real-time offer surfacing and ranking (e.g., Multi-Armed Bandits).
- Operational Leadership : Ability to foster a culture that balances high-velocity experimentation with the 99.99% reliability required for a platform serving 45M users.
Salary : $267,000 - $297,000