Staff Machine Learning Engineer - Pricing

Uber’s Dynamic Supply Pricing team is building real-time pricing that helps match supply with demand while supporting driver earnings at scale. This Staff Machine Learning Engineer role focuses on designing, developing, and bringing advanced machine learning models and pricing algorithms into production for driver pricing decisions made across a large marketplace.

You will lead technical strategy over the next 1+ year and deliver end-to-end marketplace ML solutions for distributed systems serving billions of trips. The work combines large-scale ML engineering with pricing research that blends machine learning, algorithmic game theory, and optimization.

What you’ll do

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

What you bring

• Education: Ph.D., M.S., or a Bachelor’s degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
• Experience: 6+ years leading development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (examples: 1M+ predictions/sec or 100M+ users), with a track record of strong business impact over multiple quarters
• Programming proficiency in Python, Scala, Java, or Go
• Experience with large-scale data systems such as Spark and Ray, real-time processing such as Flink, and microservices architectures
• Proficiency across the ML lifecycle at scale, including development, training, productionization, and monitoring from offline pipelines to online serving and MLOps
• Experience building and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• Deep knowledge of modern ML algorithms (such as 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

Compensation and benefits

• Salary range: USD 232,000 - 258,000 per year
• Eligible to participate in Uber’s bonus program (all US locations)
• May be offered an equity award and other types of compensation
• Eligible to participate in a 401(k) plan
• Eligible for various benefits

Additional location and work arrangement notes

• Unless approved for full remote work, employees must spend at least 50% of their time in-office
• Some roles (for example those at greenlight hubs) require full-time in-office presence
• Ask your Recruiter for details about this role’s requirements