Uber
Sr Machine Learning Engineer - Optimization
Uber, Sunnyvale, California, United States, 94087
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Sr Machine Learning Engineer - Optimization
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Uber Get AI-powered advice on this job and more exclusive features. About The Role
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 You will work with a mixed team of Backend Engineers, MLEs, and Applied Scientists You will build new scalable algorithms for real-time delivery matching products across hundreds of global marketplaces You will take things from mathematical formulation through to prototype and experiment. You will work with backend engineers to put your ideas into production You will 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) The base salary range for this role is USD$198,000 per year - USD$220,000 per year. You will also 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.
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Sr Machine Learning Engineer - Optimization
role at
Uber Get AI-powered advice on this job and more exclusive features. About The Role
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 You will work with a mixed team of Backend Engineers, MLEs, and Applied Scientists You will build new scalable algorithms for real-time delivery matching products across hundreds of global marketplaces You will take things from mathematical formulation through to prototype and experiment. You will work with backend engineers to put your ideas into production You will 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) The base salary range for this role is USD$198,000 per year - USD$220,000 per year. You will also 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.
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