Staff Machine Learning Engineer - Dynamic Pricing (San Francisco) Job at Uber, San Francisco, CA

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  • Uber
  • San Francisco, CA

Job Description

About the Role

The mission of the Surge team is to maintain overall marketplace reliability by balancing supply and demand in real-time through dynamic pricing. We build scalable real-time systems to understand market conditions, forecast demand, make predictions using ML models, solve network optimization problems, and set prices for each rider session.

Surge plays a key role in Uber’s mission to make transport accessible. We generate billions in annual gross bookings by optimizing network efficiency, significantly impacting driver earnings. Our signals are among the most important features used across Uber's optimization and ML systems. Although our team is backend-focused, our work greatly influences rider experience through pricing and reliability.

What You'll Do

You will collaborate with Engineers, Operations Researchers, and Economists to develop large-scale pricing optimization systems that set prices based on real-time marketplace conditions globally for Uber’s rides products.

  • Build and train machine learning models.
  • Identify new areas where machine learning can have a substantial impact.

Basic Qualifications

  • PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or related fields with a focus on Machine Learning.
  • 4+ years of experience in an ML role emphasizing data-driven model development and experimentation.
  • Expertise in deep learning and optimization algorithms.
  • Experience with ML frameworks like PyTorch and TensorFlow.
  • Proven ability to build and deploy end-to-end ML systems.
  • Proficiency in programming languages such as Python, Java, Go, or C++.
  • Strong communication skills and ability to collaborate effectively across teams.
  • Demonstrated ownership and perseverance on complex ML projects.

Preferred Qualifications

  • Experience with online training systems, such as real-time recommendation engines.
  • Designing and implementing performance metrics.
  • Handling time series data and forecasting, including spatial-temporal data is a plus.
  • Knowledge of models like VAE, SSM, and Normalizing Flows.
  • Optimizing inference and monitoring model performance for efficiency.
  • Experience conducting experiments and tracking models in complex environments.

For roles based in San Francisco, CA: The salary range is USD $223,000 to $248,000 annually.

You will be eligible for Uber's bonus program, potential equity awards, and other benefits. More details are available at Uber Benefits .

Uber is an Equal Opportunity/Affirmative Action employer. We consider all qualified applicants regardless of gender, race, religion, disability, veteran status, age, or other protected characteristics. If you need accommodations, please complete this form .

Our offices are central to collaboration and culture. Employees are generally expected to spend at least half their work time in the office unless fully remote work is approved. Certain roles may require 100% in-office presence. Please consult your recruiter for specific expectations.

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Job Tags

Full time, Work at office, Remote work,

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