About the Role
Delivery Marketplace is a central pillar of Uber’s delivery products, serving as the "brain" of the operation. We drive every decision that enables orders to go from point A to point B — from Uber Eats & Grocery, to newer verticals like Uber Direct and Connect. We’re responsible for everything: from dispatch decisions, predicting food ready time, delivery times, and optimizing pickup times, to ensuring we deliver the most efficient and impactful solutions for Uber’s most critical business goals. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations. The team regularly delivers $1B+ to Uber’s annual revenue growth and $XX M in annual profits.
We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and matching algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with talented ML and BE engineers, product managers, and scientists to set the team’s technical direction and solve some of Uber’s most challenging and most complex business problems in order to deliver a magical experience to users improving reliability of Uber Delivery trips.
What You Will Do
• Drive technical strategy and roadmap ownership for multiple quarters horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
• Develop novel products for online marketplaces combining machine learning for prediction and forecasting, and optimization to to improve business efficiency and the user experience.
• Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
• Develop transformer-based models (pre-training and fine-tuning) to produce embeddings and natural language profiles that power use cases across the Marketplace.
Basic Qualifications
• Ph.D., M.S. or Bachelor in Computer Science, Mathematics with focus on Machine Learning, or equivalent technical background with exceptional demonstrated impact
• 3+ years experience leading the development and deployment of ML models in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters.
• Proficiency in programming languages such as Python, Scala, Java, or Go
• Proficiency with large-scale data systems (e.g. Spark, Ray)/real-time processing (e.g. Flink)/microservices architectures
• Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
• Deep understanding of modern ML algorithms
Preferred Qualifications
• Experience in developing and deploying ML models for large scale business problems.
• Track record of translating complex business problems into technical solutions and driving cross-functional projects.
• Excellent communication skills to lead initiatives across multiple product areas
• Proficiency in deep learning, causal machine learning or reinforcement learning
• Proficiency with large embedding and language models.
For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.