About the Role
We are focused on leveraging machine learning to enhance rider experience through personalized recommendations and tailored services. Key areas we are exploring include:
- Intent modeling
- Balancing relevance and discovery
- Rider and contextual targeting
- Joint optimization with our marketplace
What You'll Do
- 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
Basic Qualifications
- Bachelor’s degree in Computer Science, Engineering, Mathematics or related field
- 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
Preferred Qualifications
- 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.
- Innate 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
- PhD degree in Computer Science, Engineering, Mathematics or related field
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.