Staff Machine Learning Engineer
Description For Staff Machine Learning Engineer
Join Uber's Rider ML team as a Staff Machine Learning Engineer in São Paulo, Brazil, where you'll be at the forefront of developing cutting-edge machine learning infrastructure and ranking solutions. The team is dedicated to enhancing rider engagement across various touchpoints within Uber's platform, including optimizing the rider homepage ranking (Project Lumos) and product selection ranking (Project Aura). You'll work on building advanced ML infrastructure and algorithms that enable real-time, dynamic personalization of rider surfaces, ensuring a tailored experience for millions of users each month. The role involves developing state-of-the-art deep learning models that operate in real-time with ultra-low latency, powering experiences that drive high revenue. This is an opportunity to work with a team that values innovation, cross-functional collaboration, and technical excellence while solving complex challenges at scale. The position offers a hybrid work arrangement and welcomes both local professionals and those willing to relocate to São Paulo. You'll be part of a company that's shaping the future of transportation and delivery services while working on projects that directly impact user experience and business outcomes.
Responsibilities For Staff Machine Learning Engineer
- Developing advanced intent modeling and ranking solutions to optimize personalized recommendations
- Striking the right balance between ranking relevance and discovery (exploration vs. exploitation)
- Researching and integrating new signals to improve key ranking metrics and user engagement
- Building and deploying ML models at scale, ensuring high reliability and quality in online serving
Requirements For Staff Machine Learning Engineer
- Bachelor's degree in Computer Science, Engineering, Mathematics or related field
- 5+ years of experience in software engineering with emphasis on data-driven methodologies
- Strong problem-solving skills, with expertise in ML methodologies
- Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems
- Industry experience in ML frameworks and complex data pipelines
- 7+ years of experience in software engineering specializing in applied ML methods
- Experience in designing scalable ML solutions using deep-learning techniques
- 3+ years of experience working in cross-functional projects
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