Staff Machine Learning Engineer - Pricing

On Uber’s Dynamic Supply Pricing team, you will help design, build, and productionize advanced machine learning and pricing algorithms that power real-time driver pricing. This Staff role focuses on delivering marketplace ML solutions at large scale, with a technical strategy roadmap spanning 1+ year and an emphasis on end-to-end engineering execution.

This position is based in New York, NY (onsite) and offers a base salary range of USD 232,000 to 258,000 per year. You may also be eligible for a bonus program, equity awards, and other compensation depending on location and role eligibility.

Responsibilities

• Own technical strategy and roadmap execution over a 1+ year horizon, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
• Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
• Develop novel pricing approaches for online marketplaces that combine machine learning, algorithmic game theory, and optimization to expand earnings opportunities for millions of drivers
• Partner with engineers, product managers, and scientists to deliver high-impact technical solutions to complex business problems

Requirements

• Ph.D., M.S., or Bachelor’s degree in Computer Science, Machine Learning, or Operations Research, or an equivalent technical background with exceptional demonstrated impact
• 6+ years leading development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (examples include 1M+ predictions/sec or 100M+ users), with a track record of outstanding business impact across multiple quarters
• Strong programming skills in Python, Scala, Java, or Go
• Proficiency with large-scale data systems such as Spark and Ray, real-time processing such as Flink, and microservices architectures
• Experience building and operating ML solutions at scale, spanning offline pipelines, online serving, and MLOps with monitoring
• Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces involving strategic agent behavior
• Deep understanding of modern ML algorithms (including DNNs, multi-task models, and transformers) and mathematical optimization (including multi-objective, LP, and convex optimization)

Technologies

• Python, Scala, Java, Go
• Spark, Ray, Flink
• Microservices architectures, MLOps
• DNNs, transformers

Benefits

• Eligible to participate in Uber’s bonus program (all US locations)
• May be offered an equity award and other types of comp
• Eligible to participate in a 401(k) plan
• Eligible for various benefits

Preferred Qualifications

• Experience creating multi-year technical strategies and owning cross-team platform architecture, with demonstrated ability to lead complex technical projects and influence the scope and output of others
• Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams
• Excellent communication skills for leading initiatives across multiple product areas and collaborating cross-functionally
• Proficiency in reinforcement learning and causal machine learning

Office collaboration: Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, such as those at greenlight hubs, may require full-time in-office presence. Ask your Recruiter for details about this role’s requirements.