About the TeamEarners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
Within Uber, the Earner Intelligence team plays a critical role in earners' journey as the team is responsible for building AI/ML systems across earner onboarding, activation, early life cycle, and resurrection.
The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits and contextual bandits, genAI LLM, long running agents, agentic harnesses, and training our own Earner language model to deep learning embeddings to build impactful data products
What the candidate will do- Design, build, and ship Earner facing agentic experiences by building conversational and ambient (long running) agents
- Build statistical, optimization, and machine learning models
- Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
- Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
Basic Qualifications
- Bachelor's or Master's or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
- 4 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on agentic AI and reinforcement learning building conversational and ambient (long running) agents, designing short and long-term memory (knowledge graph, semantic search), Reinforcement learning (Proximal Policy Optimization, Direct Preference Optimization)
- Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
- Experience with any of the following: Spark, Hive, Kafka, Cassandra.
- Experience building and productionizing innovative end-to-end Machine Learning systems.
- Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
- Experience working with cross-functional teams(product, science, product ops etc).
Preferred Qualifications
- PhD or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
- 5+ years of industry experience in machine learning, including building and deploying computer vision models and architectures.
- Expertise on expertise with post training, Knowledge Distillation, Fine tuning such as SFT, LoRa.
- Publications at industry recognized ML conferences.
- Expertise in the design and architecture of ML systems and workflows.
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 Seattle, WA-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.
Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
