Uber Marketplace is at the heart of Uber’s business, with Rider Pricing playing a critical role by setting prices and targeting promotions for Uber riders. Our team’s mission is to drive revenue growth, ridership growth and Uber’s profitability through advanced machine learning and data science. We build reliable, scalable platforms that optimize rider pricing in both real-time and offline systems, including baseline trip pricing and targeted discounts.
The Rider Pricing team is a fast-moving, high-opportunity space where you’ll have the chance to make a significant impact on the business. On this team, your work will affect over 95% of Uber’s mobility business revenue. You’ll work on the rider pricing optimization algorithms and systems, to build better pricing algorithms, optimization algorithms and models.
In this role, you'll apply advanced machine learning technologies, including deep learning, generative AI for causal modeling, representation learning and personalization, to optimize Uber’s pricing. You will also work with serving infrastructure and product teams to design and evolve the rider pricing systems to support new product and algorithm evolutions and drive Uber’s top-line rider and revenue growth.
What You’ll Do- Develop and implement machine learning and optimization solutions to solve critical business challenges, including rider pricing, discounts, promotion targeting, and personalized messaging.
- Build and scale models and systems for real-time and offline promotions, as well as rider pricing.
- Collaborate with cross-functional teams to ensure alignment and drive measurable business outcomes.
- Work on and have the opportunity to set technical directions for key ML, serving, and optimization system components that directly impact Uber’s growth.
Basic Qualifications
- Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 3+ years of full-time engineering experience.
- 2+ years of ML experience and building ML models
- Experience working with multiple multi-functional teams(product, science, product ops etc).
- Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
- Experience with big-data architecture, ETL frameworks and platforms.
- Solid understanding of latest ML technologies, and libraries.
- Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone.
- Experience with the design and architecture of ML systems and workflows.
- Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
- Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
- Experience with optimizing Spark queries for better CPU and memory efficiency.
- Experience owning and delivering a technically challenging, multi-quarter project end to end
For New York City, NY-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 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.
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
- Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of full-time engineering experience
- 2+ years of machine learning experience and experience building machine learning models
- Experience working with multiple multifunctional teams, such as product, science, and product operations
- Expertise in one or more object-oriented programming languages, such as Python, Go, Java, or C++
- Experience with big-data architecture, ETL frameworks, and platforms
- Solid understanding of current machine learning technologies and libraries
- Ability to learn quickly and take on challenging assignments
- Experience designing and architecting machine learning systems and workflows
- Experience building algorithmic solutions in production and balancing sophistication, compute complexity, maintainability, and extensibility
- Experience translating ambiguous business problems into machine learning and optimization formulations
- Experience identifying appropriate features, model structures, and optimization constraints
- Experience optimizing Spark queries for CPU and memory efficiency
- Experience owning and delivering technically challenging, multi-quarter projects end to end
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.
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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.
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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.
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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.
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