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Senior Machine Learning Engineer, Dynamic Pricing

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Uber

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Location:
United States , Sunnyvale ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

202000.00 - 224000.00 USD / Year
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Job Description:

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

Job Responsibility:

  • Work with a mixed team of Engineers, Operations Researchers, and Economists to build large-scale pricing optimization systems to set prices based on real-time marketplace conditions for Uber’s rides products globally
  • Build ML models, conduct experiments, define monitoring metrics, and ensure good operational excellence at scale
  • Help improve existing models through novel architectures and features in addition to identifying new applications and opportunities for Machine Learning

Requirements:

  • PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning
  • 3+ years of experience in an ML role with an emphasis on data and experiment driven model development
  • Expertise in deep learning and optimization algorithms
  • Experience with ML frameworks such as PyTorch and TensorFlow
  • Experience building and productionizing innovative end-to-end Machine Learning systems
  • Proficiency in one or more coding languages such as Python, Java, Go, or C++
  • Strong communication skills and can work effectively with cross-functional partners
  • Strong sense of ownership and tenacity toward hard machine-learning projects

Nice to have:

  • Experience in serving and monitoring online training systems such as real time recommendation systems
  • Experience designing and implementing novel metrics for performance evaluation
  • Experience handling time series data and time series forecasting (experience handling spatial temporal data is plus)
  • Deep understanding of models such as VAE (Variational Auto Encoder), SSM (State space model), and Normalizing Flow
  • Experience in inference optimization and monitoring model performance efficiency and being able to identify bottlenecks
  • Proven track record in conducting experiments and tracking models in high-complexity environments
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible to participate in a 401(k) plan
  • Eligible for various benefits

Additional Information:

Job Posted:
March 25, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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