Uber Grocery's Catalog team needs to build and scale AI/ML systems to understand and manage vast, complex, and ever-evolving grocery data, impacting every consumer-facing experience in the Uber Eats app.
Requirements
- Deep Learning
- Scalable ML architecture
- Experience in applying machine learning models to solve large-scale real-world problems
- Personalization, user understanding and targeting
- Optimization (RL/Bayes/Bandits)
- Causal inference
- Programming language (e.g. C, C++, Java, Python, or Go)
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
- build models that determine what each item really is-its brand, flavor, color, and what kinds of customers might prefer it
- build and maintain large-scale ML forecasting systems to predict availability and reduce substitutions
- pushing the frontier of real-time store mapping using computer vision
Other
- lead the ML strategy and execution for Uber Grocery's Catalog team
- guide a team of talented ML engineers and collaborate cross-functionally with product, design, operations, and platform teams
- 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
- For New York, NY-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.
