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:
You will be on a super collaborative team designed to maximize your ability to deliver results. If you are motivated by building technically challenging machine learning solutions in real-time and at scale, working on projects that impact every single Uber delivery, knowing that every eater and courier sees and benefits from your work, and helping to drive Uber's top business metrics, then delivery pricing is the team for you at Uber!
Minimum qualifications:

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field OR 3-years full-time Software Engineering work experience, WHICH INCLUDES 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 2-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.

Technical skills:
Required:

• Scalable ML architecture
• Feature management

Preferred:

• Deep Learning

For Colorado-based applicants: Please refer to this role in our careers page for more details on your total compensation and benefits package. You can get there by clicking 'apply' if you're not already on our careers site. #LI-Remote