Rider Experience drives and enables the critical trip booking funnel within the Rides app that makes up almost all of the trip transactions and contributes tremendously to business growth. Our team actively explores personalization algorithmic and UX improvements in product recommendations and merchandising to help millions of riders find and discover the right products every hour to move around the world, and power smart and intuitive experiences for them.
Requirements
- 3+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
- Strong problem-solving skills, with expertise in ML methodologies
- Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
- Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java
- 5+ years of experience in software engineering specializing in applied ML methods
- Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
- Experience with deep-learning techniques, having worked with embeddings and transformer architectures
Responsibilities
- Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising: help riders find and complete rides with the right products, understanding their ride context and modeling their intent while attending to Uber's business goals, marketplace conditions and efficiencies.
- Provide technical leadership to a passionate, experienced, and diverse engineering team. Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions. Classification, regression, and multi-task learning are in our toolbox.
- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough & precise monitoring, and applying model debugging & interpretation techniques.
- Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions
Other
- Bachelor's degree in Computer Science, Engineering, Mathematics or related field
- Innately truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions.
- 1+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies
- Passionate about helping junior members grow by inspiring and mentoring engineers
- Resilience, determination, ownership mindset
