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Staff Optimization Engineer, Dynamic Pricing

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Uber

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Location:
United States , San Francisco

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Contract Type:
Not provided

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Salary:

232000.00 - 258000.00 USD / Year

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
  • Build new scalable algorithms for real-time pricing of Ubers products across hundreds of global marketplaces
  • Help set the team's technical direction and roadmap
  • Communicate with leadership, identify new opportunities, and help guide the growth of more junior engineers

Requirements:

  • PhD in relevant fields (Operations Research, Industrial Engineering, Computer Science) with a focus on optimization modeling
  • 5+ years of industry experience developing algorithms and models for large-scale deployment
  • Experience with optimization packages such as Gurobi, CPLEX, and OR Tools
  • Experience with two-sided marketplace design, pricing optimization, matching/allocation, etc…
  • Strong communication skills and ability to work effectively with cross-functional partners
  • Proficiency in one or more coding languages such as Python, Java, Go, or C++

Nice to have:

  • Familiarity with Machine Learning models, experimentation (e.g., A/B testing) and causal inference
  • Experience with real-time optimization systems (optimization under tight time constraints)
  • Experience mentoring and growing junior engineers
  • Experience with creating and defining technical direction and roadmaps
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible for various benefits

Additional Information:

Job Posted:
January 31, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
Job Link Share:

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