Sr Machine Learning Engineer

Posted 5 Days Ago
Be an Early Applicant
3 Locations
In-Office
202K-224K Annually
Senior level
Logistics • Transportation • 3PL: Third Party Logistics
We reimagine the way the world moves for the better.
The Role
Lead machine learning and optimization initiatives for Uber’s rider pricing systems. Develop, improve, evaluate, and deploy scalable pricing and promotion-targeting algorithms. Own technical problems end to end, shape product and technical roadmaps, collaborate across ML, serving, and product teams, and mentor engineers. Apply deep learning, generative AI, causal modeling, representation learning, personalization, and reinforcement learning to improve pricing, affordability, ridership, and revenue.
Summary Generated by Built In
About the Role

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 take ownership of one key pillar of the rider pricing domain and lead the technical direction for improving our pricing algorithms, optimization algorithms and models. You will work across ML, serving, and optimization system components, and set technical direction for modeling best practices across model building, evaluation and deployment. 

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
  • Take a lead on pricing ML and optimization problems, by developing and implementing new machine learning and optimization techniques powering billions of rides around the world, and helping riders achieve their mobility needs. 
  • Improve the performance of models and algorithms powering pricing algorithms and promotion targeting.
  • Own the problem E2E, including working with cross-functional teams to define the product and/or technical roadmap.
  • Mentor more junior team members by role modeling ML best practices. Collaborate with cross-functional teams to ensure alignment and drive Uber’s ridership and revenue growth. Help Uber’s end-users by making mobility options accessible and affordable.

Basic Qualifications

  • Masters degree in Computer Science, Engineering, Mathematics, or a related field, with 5+ years of full-time engineering experience.
  • Proficiency in one or more programming languages (e.g., C, C++, Java, Python, Go).
  • Experience with machine learning and optimization algorithms.
Preferred Qualifications
  • PhD in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience.
  • Experience solving complex business problems by translating them into machine learning and optimization solutions.
  • Familiarity with large-scale data systems (e.g., Spark, Hive) and experience building production-ready algorithmic systems.
  • Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.
Responsibilities

For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 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 Us

Ready 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

  • Master’s degree in Computer Science, Engineering, Mathematics, or a related field
  • 5+ years of full-time engineering experience
  • Proficiency in one or more programming languages, such as C, C++, Java, Python, or Go
  • Experience with machine learning and optimization algorithms
  • PhD in Computer Science, Engineering, Mathematics, or a related field
  • 2+ years of full-time engineering experience with a PhD
  • Experience translating complex business problems into machine learning and optimization solutions
  • Familiarity with large-scale data systems such as Spark and Hive
  • Experience building production-ready algorithmic systems
  • Strong background in deep learning, generative AI, causal modeling, and reinforcement learning

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

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The Company
HQ: San Francisco, CA
21,000 Employees
Year Founded: 2009

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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