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# Sr Machine Learning Engineer - Consumer Incentives

- **Company:** Uber
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $202,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Software Deployment, Information Technology, Machine Learning Operations, Programming Languages
- **Published:** November 6, 2026
- **Apply:** https://www.juju.com/job/1_uber-5wqzse6063db0642fe9644bd7c5a2492391c5KMAKWAAAAADAAAAAAAAAAAAAAAADD25TCM

## About the Role

+ Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 4+ years of full-time engineering experience.
 + Proficiency in at least one programming language such as Python, Go, or Java
 + Experience in building and productionizing innovative end-to-end ML systems.
 + Strong communication skills and ability to work effectively with cross-functional partners
 + Strong sense of ownership to drive projects end-to-end
**Preferred Qualifications**

 + Track record of designing and delivering large-scale consumer products
 + Demonstrated leadership skills, with experience in mentoring and guiding junior engineers.
 + Proven experience in experimental design and causal inference

## Description

Operating across key business areas like grocery and food, the Consumer Incentives team drives Uber's growth and long-term profitability.
We build products that power seamless, affordable, and enjoyable customer experiences by building sophisticated distributed systems and AI-powered optimizations to scale products for hundreds of millions of global users.
**What you'll do**
In this role, you will build products powered by scalable distributed systems and advanced AI solutions.
Your work will optimize user experiences across multiple verticals, such as grocery and food, while fostering sustainable business growth.
Key responsibilities include:

 + Architecting and launching products to power key consumer experience and business outcomes.
 + Overseeing full project lifecycles spanning initial scoping, offline evaluation, experimental testing, production deployment, and post-launch maintenance.
 + Designing, tuning, and enhancing systems and algorithms to operate at scale.
 + Partnering with cross-functional stakeholders across product management, operations, and data science.