Uber Grocery's Catalog team needs to build and scale AI/ML systems to make sense of vast, complex, and ever-evolving grocery data, impacting consumer-facing experiences from app opening to checkout.
Requirements
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
deep semantic understanding of catalog items
large-scale inventory forecasting
novel computer vision applications that integrate directly with courier workflows
Catalog Understanding & Enrichment: We build models that determine what each item really is—its brand, flavor, color, and what kinds of customers might prefer it.
Product Relationships: Our systems learn how products relate to one another—what’s a substitute, what’s often bought together, and what combinations drive better outcomes for both customers and merchants.
Inventory Forecasting: Grocery inventory is volatile and high-stakes. Our team builds and maintains large-scale ML forecasting systems to predict availability and reduce substitutions—at a scale few companies ever reach.
Other
4+ years of people management experience
PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 4-years full-time Software Engineering work experience OR 10-years full-time Software Engineering work experience
