Uber (501+ Employees, 24% 2 Yr Employee Growth Rate)
About the role:
Partners with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve complex problems with multiple dependencies. This role also leads team efforts to leverage and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.
About the Team:
Uber is changing the way people think about transportation. Not that long ago, we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of cities everywhere. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.
Uber is hiring Machine Learning Engineers to join the Advanced Matching team in our Toronto tech office to build out a new platform for in-advanced matching of riders and drivers to power all of Uber’s reservation-based products globally. The platform matches future reservations with the optimal driver to maximize reliability and driver flexibility, while simultaneously improving the overall efficiency of the Uber Marketplace.
PhD or equivalent in Computer Science, Engineering, Mathematics or related fieldOR* 4-years full-time Software Engineering work experience,
2-years total technical software engineering experience in one or more of the following areas:
• Programming language (e.g. C, C++, Java, Python, or Go)
• Training using data structures and algorithms
• Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
• Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
• Note the 4-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.
• Scalable ML architecture
• Feature management
• Deep Learning