Staff Machine Learning Engineer

The Staff Machine Learning Engineer will join Uber’s Rider Pricing team in San Francisco, leading technical direction to advance pricing and optimization algorithms and models. The role focuses on improving rider pricing in both real-time and offline contexts through collaboration across machine learning, serving, and optimization systems.

Role Summary

You will lead a group of Software Engineers and Machine Learning Engineers working on rider pricing. The work supports models and optimization techniques that power pricing decisions at massive scale, contributing to better mobility outcomes for riders and helping drive ridership and revenue growth.

Responsibilities

• Lead a group of SWEs and MLEs to develop and implement new machine learning and optimization techniques supporting Uber’s rider pricing for billions of rides worldwide.
• Improve the performance of models and algorithms used in pricing algorithms and promotion targeting.
• Own the end-to-end problem, including partnering with cross-functional teams to define the product and/or technical roadmap.
• Mentor more junior team members by role modeling machine learning best practices.
• Collaborate with cross-functional teams to ensure alignment and drive Uber’s ridership and revenue growth.
• Support end-users by making mobility options accessible and affordable.

Required 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, for example: C, C++, Java, Python, or 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 such as Spark and Hive, plus experience building production-ready algorithmic systems.
• Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.

Technologies

• C, C++, Java, Python, Go
• Spark, Hive

Compensation and Location

• Location: San Francisco, CA (onsite)
• Salary: USD 232,000 - 258,000 per yearly

Benefits

• Eligible to participate in Uber’s bonus program
• May be offered an equity award and other types of compensation
• 401(k) plan
• Various benefits

Working Arrangement

Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, including those at greenlight hubs, require full-time in-office presence.

US Plan Eligibility Note

For all US locations, all full-time employees are eligible to participate in a 401(k) plan.