Uber
Staff Machine Learning Engineer - Pricing
$232K–$258K
New York City, New York +3 · Staff · Full-time · Posted Oct 12, 2026
- Location
- New York City, New York
Seattle, Washington
Sunnyvale, California
San Francisco, California - Experience
- 6+ years; the posting cites production scale such as 1M+ predictions/sec or 100M+ users.
- Education
- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact.
About the job
Leads the development and productionization of machine-learning models and pricing algorithms for Uber’s real-time marketplace, shaping technical strategy and large-scale systems.
What you'll do
- Own technical strategy, roadmap, architecture decisions, implementation, executive alignment, and technical mentorship.
- Lead end-to-end ML solutions and pricing algorithms for large-scale, real-time distributed systems.
- Collaborate across engineering, product, and science teams to solve complex marketplace problems.
What they ask for
- Degree in Computer Science, Machine Learning, or Operations Research (Ph.D., M.S., or Bachelor’s), or equivalent technical background with exceptional demonstrated impact.
- 6+ years leading development and deployment of ML models and optimization algorithms in large-scale production environments; demonstrated business impact.
- Proficiency in Python, Scala, Java, or Go, and large-scale data systems, real-time processing, and microservices architectures.
- Experience deploying pricing algorithms for multi-sided real-time marketplaces; strong knowledge of modern ML algorithms and mathematical optimization.
Nice to have
- Experience in multi-year technical strategy, platform architecture, and cross-team technical leadership.
- Proficiency in reinforcement learning and causal machine learning.
Pay
USD $232,000 per year - USD $258,000 per year (base salary)
Tools
Python, Scala, Java, Go, Spark, Ray, Flink, MLOps
AI focus
Develops machine-learning models and pricing algorithms, including deep learning, causal modeling, and reinforcement learning, for real-time marketplace pricing and optimization.
Model-written summary · the original posting is authoritative