Sr. Scientist, UberEats Applied AI (Machine Learning) Job at Uber (San Francisco)

Job Description

Working at Uber means solving hard problems in a high-stakes, fast-moving environment. You’ll need to take ownership, stay adaptable, and build with both urgency and care. If you’re energized by a challenge and motivated by real-world impact, this is where you’ll grow! As a Scientist on the Discovery Science team, you will move the needle for the business through strong product execution at the intersection of ML research and marketplace algorithms. This isn't about tuning models in a vacuum; it’s about navigating the messiness of a multi-sided ecosystem where performance, safety, and scale are inseparable. You will partner with engineers to architect the next generation of RecSys, balancing technical rigor with the pressure of real-world traffic and shifting business priorities.

Job Responsibility

Design and implement ML algorithms and objective functions that unify competing business interests like organic relevance and sponsored content into a single value space
Act as the science lead for foundational machine learning initiatives, unblocking technical debt and optimizing feature engineering for high-scale, real-time systems
Navigate the ambiguity of user behavior by designing sophisticated experiments and causal inference frameworks that go beyond standard A/B testing
Collaborate across disciplines (Product, Engineering, and Data Science) to translate high-level business goals into theoretically sound and performant technical roadmaps
Research and apply advancements in Deep Learning, Reinforcement Learning, and GenAI to solve complex, high-impact problems without a clear starting point
Own your algorithms/ML workflow, from the first scientific hypothesis to debugging production issues in real-time, low-latency environments

Requirements

Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields
Minimum 4 years of industry experience as an Applied or Data Scientist or equivalent (2+ years if holding a Ph.D.)
Proficiency in Python or R with experience handling large-scale datasets using Spark, Hive, or PySpark
Proven experience in building and training Deep Learning models
Solid understanding of statistical methods, experimental design, and A/B testing

Nice to have

Domain expertise in Ranking, Recommender Systems (RecSys), or Search
Experience with advanced modeling techniques like Reinforcement Learning, multi-task learning, or auto-regressive models
Ability to communicate complex scientific results to both technical and non-technical stakeholders to influence business strategy
Familiarity with deploying production-grade pipelines into real-time, low-latency systems using Kafka or Pinot
Strong systems thinking and the ability to make smart trade-offs between short-term velocity and long-term scientific rigor

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits (details at provided link)

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Sr. Scientist, UberEats Applied AI (Machine Learning)

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