About the Role
Uber One is Uber's flagship membership program, serving more than 50 million members globally across Mobility, Delivery, Grocery, and other Uber experiences. Membership combines savings, benefits, priority experiences, and exclusive offerings while driving engagement, cross-platform adoption, and long-term retention.
As a Senior Machine Learning Engineer, you will build product-focused ML systems for targeting, personalization, offers, and member engagement. Your models will directly influence the Membership experiences consumers see across Uber and Uber Eats.
What You Will Do- Own targeting and personalization models from problem framing through deployment and monitoring.
- Build treatment-effect and uplift models to estimate incremental impact of Membership interventions.
- Design budget-aware allocation systems for consumer offers under real business constraints.
- Build ranking and sequencing models for Membership messaging across Mobility and Delivery.
- Productionize models in real-time serving paths and large-scale batch pipelines.
- Design and analyze experiments to measure incremental product impact.
- Translate ambiguous Membership growth problems into concrete ML solutions with cross-functional partners.
- 5+ years of experience building and shipping production ML models.
- Strong proficiency in Python and modern ML frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM.
- Strong SQL and large-scale data processing experience with Spark, Hive, Presto, or similar technologies.
- Experience with experimental design, A/B testing, and measurement of noisy product outcomes.
- Experience owning ML systems from offline development through serving, monitoring, and retraining.
- Experience applying ML to user-facing product or business decisions.
- Bachelor's degree in a quantitative field or equivalent practical experience.
- Experience applying ML to membership, subscription, growth, or consumer engagement products.
- Experience with uplift modeling, treatment effects, ranking, recommendation, or sequential decision systems.
- Experience with constrained optimization, incentives, promotions, pricing, or offer targeting at consumer scale.
- Strong product mindset with experience translating consumer needs and business constraints into measurable ML outcomes.
- Experience collaborating across Product, Engineering, Data Science, Finance, or Marketing on complex product decisions.
- Familiarity with subscription metrics including conversion, retention, LTV, cannibalization, and incrementality.
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
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.
About UsReady to Ride?
This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Skills Required
- 5+ years of experience building and shipping production machine learning models
- Strong proficiency in Python and modern machine learning frameworks such as PyTorch, scikit-learn, XGBoost, or LightGBM
- Strong SQL and large-scale data processing experience with Spark, Hive, Presto, or similar technologies
- Experience with experimental design, A/B testing, and measurement of noisy product outcomes
- Experience owning machine learning systems from offline development through serving, monitoring, and retraining
- Experience applying machine learning to user-facing products or business decisions
- Bachelor's degree in a quantitative field or equivalent practical experience
- Experience applying machine learning to membership, subscription, growth, or consumer engagement products
- Experience with uplift modeling, treatment effects, ranking, recommendation, or sequential decision systems
- Experience with constrained optimization, incentives, promotions, pricing, or offer targeting at consumer scale
- Strong product mindset with experience translating consumer needs and business constraints into measurable machine learning outcomes
- Experience collaborating across Product, Engineering, Data Science, Finance, or Marketing on complex product decisions
- Familiarity with subscription metrics including conversion, retention, lifetime value, cannibalization, and incrementality
Uber Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uber and has not been reviewed or approved by Uber.
-
Parental & Family Support — Policies provide a minimum of fully paid parental leave for all parents and financial support for fertility, adoption, and surrogacy, with added credits to ease the transition. Programs extend to family medical leave and parenting support resources, indicating depth beyond baseline offerings.
-
Healthcare Strength — Healthcare coverage is described as comprehensive across many countries, with medical, dental, vision, life, disability, and mental health benefits, plus allowances where direct plans are not available. Wellness programs and reimbursements further reinforce access to care.
-
Wellbeing & Lifestyle Benefits — Monthly ride and meal credits, free office meals/snacks, fitness stipends, onsite gyms, and wellbeing reimbursements create meaningful everyday value. Home‑office stipends, travel medical coverage, and counseling support round out lifestyle-oriented perks.
Uber Insights
What We Do
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything. Movement is what we do. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real-time. At the incredible speed of now.
Why Work With Us
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.
Gallery
