Base Salary
$202k - $224k/yr
Responsibilities
- Design, build, and ship conversational and ambient long-running agentic experiences for earners.
- Build statistical, optimization, reinforcement learning, and machine learning models.
- Develop agent memory systems using knowledge graphs and semantic search.
- Work with multifunctional leads to establish technical vision, develop methodologies, and drive team direction.
- Collaborate with product, engineering, operations, marketing, and product operations teams to develop ML systems from concept through production.
- Design and architect end-to-end ML systems and workflows.
Requirements
- Bachelor’s or master’s degree, or equivalent experience, in computer science, machine learning, operations research, statistics, or a related quantitative field.
- At least four years of industry experience as a machine learning engineer or research scientist, with strong experience in agentic AI and reinforcement learning.
- Experience building conversational and ambient long-running agents and designing short- and long-term memory systems.
- Experience with reinforcement learning methods including Proximal Policy Optimization and Direct Preference Optimization.
- Proficiency in multiple object-oriented programming languages such as Python, Go, Java, and C++.
- Experience with Spark, Hive, Kafka, or Cassandra.
- Experience building and productionizing innovative end-to-end machine learning systems.
- Experience with exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
- Experience working with cross-functional teams.
- Preferred: PhD or equivalent experience in a relevant quantitative field.
- Preferred: five or more years of industry machine learning experience, including building and deploying computer vision models and architectures.
- Preferred: expertise in post-training, knowledge distillation, and fine-tuning methods such as SFT and LoRA.
- Preferred: publications at industry-recognized machine learning conferences and expertise in ML system and workflow architecture.
Benefits
- Eligible for Uber’s bonus program and potential equity awards and other compensation types.
- 401(k) plan for all full-time employees.
- Various employee benefits are available.
- The role is listed for locations in New York City, San Francisco, Seattle, and Sunnyvale.
Tech Stack
Categories
About Uber
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.