Uber
About The Role
Delivery Marketplace is a central pillar of Uber's delivery products, serving as the "brain" of the operation. We drive decisions that enable orders to go from point A to point B—from Uber Eats to newer verticals like Uber Grocery. We’re responsible for dispatch decisions, predicting delivery times, and optimizing pickup times to deliver efficient and impactful solutions for Uber's goals.
As a
Staff Machine Learning Engineer (MLE) , you will lead cutting-edge efforts within the Delivery Marketplace organization, developing optimization solutions using real-time and machine learning signals to solve complex, strategically important challenges. You will work on critical systems that directly impact Uber's top and bottom lines and collaborate with engineers, product managers, and data scientists to build solutions at scale.
This role offers the opportunity to tackle complex, real-time optimization problems at Uber scale. You will lead a team of MLEs, work with diverse stakeholders, and influence the future of Uber's delivery experience.
What You Will Do
Lead the design and development of machine learning solutions that optimize real-time operations across Uber's Delivery Marketplace.
Build advanced ML models using techniques such as reinforcement learning, deep learning, and optimization methods to improve efficiency and the user experience.
Lead and mentor a team of MLEs, providing technical leadership, setting the vision, and guiding the end-to-end development process from ideation to deployment and scaling.
Collaborate with cross-functional teams (product managers, data scientists, engineers) to define high-impact problems and develop solutions that improve operational efficiency and user experience.
Apply forecasting, demand-supply models, and prediction models for factors such as food prep time, batching quality, and courier activity at restaurants.
Balance business objectives and user experience by developing objective functions that optimize both business performance and user satisfaction.
Basic Qualifications
PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2 years of full-time Software Engineering experience OR 5 years of full-time Software Engineering experience, including 3 years of total technical software engineering experience in one or more of the following areas:
Programming languages (e.g., C, C++, Java, Python, or Go)
Large-scale training using data structures and algorithms
Modern machine learning algorithms (e.g., tree-based, supervised, deep, or probabilistic learning)
Machine Learning software such as TensorFlow, PyTorch, Caffe, Scikit-Learn, or Spark MLlib
Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc.
Experience in the development, training, productionization and monitoring of ML solutions at scale.
Preferred Qualifications
Experience in a technical leadership role and mentoring junior engineers.
Experience with modern deep learning architectures and probabilistic models.
Experience in optimization (reinforcement learning, Bayesian methods, Bandits) and online learning.
Experience in causal inference, personalization, and ranking.
Compensation details vary by location. Uber provides a bonus program, potential equity awards, and other benefits. More details at https://www.uber.com/careers/benefits.
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As a
Staff Machine Learning Engineer (MLE) , you will lead cutting-edge efforts within the Delivery Marketplace organization, developing optimization solutions using real-time and machine learning signals to solve complex, strategically important challenges. You will work on critical systems that directly impact Uber's top and bottom lines and collaborate with engineers, product managers, and data scientists to build solutions at scale.
This role offers the opportunity to tackle complex, real-time optimization problems at Uber scale. You will lead a team of MLEs, work with diverse stakeholders, and influence the future of Uber's delivery experience.
What You Will Do
Lead the design and development of machine learning solutions that optimize real-time operations across Uber's Delivery Marketplace.
Build advanced ML models using techniques such as reinforcement learning, deep learning, and optimization methods to improve efficiency and the user experience.
Lead and mentor a team of MLEs, providing technical leadership, setting the vision, and guiding the end-to-end development process from ideation to deployment and scaling.
Collaborate with cross-functional teams (product managers, data scientists, engineers) to define high-impact problems and develop solutions that improve operational efficiency and user experience.
Apply forecasting, demand-supply models, and prediction models for factors such as food prep time, batching quality, and courier activity at restaurants.
Balance business objectives and user experience by developing objective functions that optimize both business performance and user satisfaction.
Basic Qualifications
PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2 years of full-time Software Engineering experience OR 5 years of full-time Software Engineering experience, including 3 years of total technical software engineering experience in one or more of the following areas:
Programming languages (e.g., C, C++, Java, Python, or Go)
Large-scale training using data structures and algorithms
Modern machine learning algorithms (e.g., tree-based, supervised, deep, or probabilistic learning)
Machine Learning software such as TensorFlow, PyTorch, Caffe, Scikit-Learn, or Spark MLlib
Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc.
Experience in the development, training, productionization and monitoring of ML solutions at scale.
Preferred Qualifications
Experience in a technical leadership role and mentoring junior engineers.
Experience with modern deep learning architectures and probabilistic models.
Experience in optimization (reinforcement learning, Bayesian methods, Bandits) and online learning.
Experience in causal inference, personalization, and ranking.
Compensation details vary by location. Uber provides a bonus program, potential equity awards, and other benefits. More details at https://www.uber.com/careers/benefits.
#J-18808-Ljbffr