This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Uber Eats is the fastest-growing food delivery platform in the world! Our team's work at Uber Eats directly impacts and continues to transform our communities. The Merchant Intelligence team is at the heart of this mission, building the foundational systems that help Uber Eats better understand, represent, and categorize every merchant on our platform. As a Machine Learning Engineer on this team, you will focus on improving the quality, consistency, and usability of merchant-related data at a global scale. You will leverage our ML platform to build models that serve critical use cases across Uber, including Sales and Outreach, Onboarding, Ads and Offers, and Feed Optimization. This is a unique opportunity to work on large-scale systems where your ML solutions will directly power merchant selection and product experiences for millions of users.
Job Responsibility:
Innovate and Productionize ML Models
Build Scalable ML Systems
Feature Engineering
Enhance Data Foundations
Cross-Functional Collaboration
Incremental Impact
Requirements:
PhD or Master in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences and 4 years minimum of industry experience with a strong focus on machine learning and recommendation systems
Strong coding skills in at least one language such as Python, Java, or Go
Expertise with modern ML frameworks such as PyTorch or TensorFlow
Experience building and productionizing innovative, end-to-end Machine Learning systems that handle large or complex datasets
Nice to have:
Domain Expertise in simplifying and converting complex business problems into actionable ML problems
Large-Scale Systems development scaling to millions of users
Familiarity with data processing and streaming tools such as Spark, Hive, Kafka, or Cassandra
Experience with NLP, graph machine learning, or entity resolution