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Sr Machine Learning Engineer - Optimization

Build and deploy real-time optimization algorithms for Uber's delivery matching system
San Francisco, California, United States
Senior
$198,000 – 220,000 USD / year
14 hours agoBe an early applicant
California Staffing

California Staffing

Arkansas Staffing appears to be a government-associated entity focused on workforce development and employment services within the state of Arkansas.

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Optimization/Operations Research Engineer

Delivery Marketplace is a central pillar to Uber's delivery products. As the central brain of the company, we are the decision makers that make moving from point A to point B possible for every order that Uber serves, from UberEats to new verticals such as Grocery. We handle all the logic from making the dispatch decisions, predicting how long a delivery might take, and estimating optimal pickup times for orders. We build products that directly impact Uber's top and bottom lines. Optimization/Operations Research Engineers lead efforts within the team and broader Delivery Marketplace organization to drive ideation, development and productionization of optimization solutions with real-time and ML-based signals that solve strategically important problems. Some existing problem spaces that the team works on:

  • Develop the objective function which balances magical user experience and economics of the business
  • Improve timeliness for Uber delivery trips
  • Eater and courier segmentations based delivery matching decisions

It is a challenging yet rewarding job. You will have a lot of opportunities to work with product managers, Applied Scientists and ML and BE engineers. You will be in charge of solving Uber-scale problems with the right techniques and algorithms.

What You Will Do:

  • Work with a mixed team of Backend Engineers, MLEs, and Applied Scientists
  • Build new scalable algorithms for real-time delivery matching products across hundreds of global marketplaces
  • Take things from mathematical formulation through to prototype and experiment. You will work with backend engineers to put your ideas into production
  • Help identify new opportunities for improving our algorithms and models

Basic Qualifications:

  • PhD in relevant fields (Operations Research, Computer Science, Mathematics, Industrial Engineering, etc.) with a focus on optimization modeling
  • 3+ years of industry experience developing algorithms and models for large-scale deployment
  • Experience with optimization packages such as Gurobi, CPLEX, and OR Tools
  • 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+

Preferred Qualifications:

  • Experience with two or three-sided marketplace design, matching/allocation, pricing optimization, etc
  • 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)

Base salary range for this role is USD$198,000 per year - USD$220,000 per year for all US locations. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link.

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know.

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Sr Machine Learning Engineer - Optimization
San Francisco, California, United States
$198,000 – 220,000 USD / year
Engineering
About California Staffing
Arkansas Staffing appears to be a government-associated entity focused on workforce development and employment services within the state of Arkansas.