Staff Machine Learning Engineer

Uber Technologies Inc.; San Francisco (CA); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Comprehensive benefits

Job summary

Uber Technologies Inc. is seeking a senior engineer to lead the Rider Pricing ML/optimization effort within Uber Marketplace. You will own end-to-end pricing models and work with ML, serving, and product teams to drive revenue and rider growth.

You will mentor engineers, improve model performance, and help shape pricing strategies across real-time and offline systems, with base salary in the USD 232,000–258,000 range plus bonus, equity, and benefits. In-office presence is required for most roles.

Qualifications

• Master's degree in Computer Science, Engineering, Mathematics, or a related field, with 7+ 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.

Responsibilities

• Lead a group of SWEs and MLEs working on Uber’s rider pricing to develop and implement new ML and optimization techniques powering billions of rides.
• Improve the performance of models and algorithms powering pricing algorithms and promotion targeting.
• Own the problem end-to-end, including cross-functional roadmap definition.
• Mentor junior engineers and propagate ML best practices across teams.

Skills

Programming languages

Machine learning

Optimization algorithms

Education

Master's degree (CS/Engineering/Math)

PhD (CS/Engineering/Math)

Tools

Spark

Hive

Job description

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

• Lead a group of SWEs and MLEs working on Uber’s rider pricing to develop and implement 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 7+ 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.

For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 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.

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.