Uber is looking to solve the problem of powering every single consumer-facing experience in the Uber Eats app, including building and scaling a diverse range of AI/ML systems to make sense of vast, complex, and ever-evolving grocery data.
Requirements
- PhD or equivalent in Computer Science, Engineering, Mathematics or related field
- Programming language (e.g. C, C++, Java, Python, or Go)
- Large-scale 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
- Deep Learning
- Scalable ML architecture
- Experience in applying machine learning models to solve large-scale real-world problems
Responsibilities
- Building and scaling a diverse range of AI/ML systems that make sense of vast, complex, and ever-evolving grocery data
- Guiding a team of talented ML engineers and collaborating cross-functionally with product, design, operations, and platform teams to shape the future of grocery shopping on Uber Eats
- Developing state of the art technology to optimize the pricing and incentives strategy in the platform
- Leading the ML strategy and execution for Uber Grocery's Catalog team
- Building models that determine what each item really is-its brand, flavor, color, and what kinds of customers might prefer it
- Building and maintaining large-scale ML forecasting systems to predict availability and reduce substitutions
- Pushing the frontier of real-time store mapping using computer vision
Other
- 4-years full-time Software Engineering work experience OR 10-years full-time Software Engineering work experience
- 4+ years of people management experience
- Travel requirements not specified
- Visa requirements not specified
- Degree requirements: PhD or equivalent in Computer Science, Engineering, Mathematics or related field
