Machine Learning Engineer II, Pricing

Uber’s Dynamic Supply Pricing team is seeking a Machine Learning Engineer II, Pricing to design, build, and productionize advanced machine learning models and pricing algorithms that support real-time driver pricing at scale.

Key Responsibilities

• Design, develop, and productionize end-to-end machine learning solutions for large-scale distributed systems supporting billions of trips.
• Develop novel pricing approaches for online marketplaces that integrate machine learning, algorithmic game theory, and optimization to create earnings opportunities for millions of drivers.
• Collaborate with senior engineers to define project scope and execution, and mentor junior team members on design and implementation.
• Work with a team of engineers, product managers, and scientists to deliver high-impact technical solutions to complex business problems.

Required Qualifications

• Ph.D., M.S., or Bachelor’s degree in Computer Science, Machine Learning, or Operations Research, or an equivalent technical background with exceptional demonstrated impact.
• 2+ years of experience developing and deploying machine learning models and optimization algorithms in large-scale production environments.
• Proficiency in programming languages such as Python, Scala, Java, or Go.
• Experience with large-scale data systems (e.g., Spark, Ray), real-time processing (e.g., Flink), and microservices architectures.
• Experience developing, training, productionizing, and monitoring machine learning solutions at scale, including offline pipelines, online serving, and MLOps.
• Familiarity with modern ML algorithms (e.g., DNNs, multi-task models, transformers) and mathematical optimization (e.g., LP, convex optimization), with an established ability and ambition to deepen expertise.

Preferred Qualifications

• Experience translating ambiguous business problems into technical solutions using structured, principled methods.
• Strong communication skills through documentation and design discussions.
• Experience building and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior.
• Experience in reinforcement learning and causal machine learning.

Technology Focus

• Programming: Python, Scala, Java, Go
• Data and compute: Spark, Ray
• Real-time processing: Flink
• Architecture and ML operations: microservices architectures, MLOps
• ML and optimization: DNNs, multi-task models, transformers, LP, convex optimization

Compensation and Location

Location: Sunnyvale, CA (onsite).
Salary: USD 171,000 - 190,000 per year.

For all US locations, the base salary range applies for eligible roles, including Sunnyvale, CA-based roles.

Benefits

• Eligible to participate in Uber’s bonus program.
• May be offered an equity award and other forms of compensation.
• Eligible for a 401(k) plan.
• Eligible for various benefits.

Work Arrangement

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, such as those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role’s requirements.