Senior Machine Learning Engineer - Pricing

Uber; San Francisco (CA); On-site; USD 202,000 - 224,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber’s Dynamic Supply Pricing (DSP) team is building machine learning and algorithmic approaches to power real-time driver pricing at massive scale. In this Senior Machine Learning Engineer role, you’ll help design, develop, and productionize advanced ML models and pricing algorithms that support earnings opportunities for drivers while serving billions of trips.

You’ll lead end-to-end ML solutions, collaborate with product and engineering teams, mentor junior engineers, and apply ML methods to

Qualifications

• Ph.D., M.S., or Bachelor's degree in Computer Science, Machine Learning, or Operations Research (or equivalent technical background) with exceptional demonstrated impact.
• 4+ years of experience developing and deploying machine learning models and optimization algorithms in large-scale production environments, including measurable business impact over multiple quarters and substantial technical contributions.
• 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.
• Experience spanning development, training, productionization, and monitoring of ML systems at scale, from offline pipelines to online serving and MLOps.
• Deep understanding of modern ML algorithms (such as DNNs, multi-task models, and transformers) and mathematical optimization (such as LP and convex optimization)

Responsibilities

• Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems supporting billions of trips.
• Develop novel pricing approaches for online marketplaces by combining machine learning with algorithmic game theory and optimization.
• Partner with team leads to define the team’s technical direction and own implementation work.
• Provide technical mentorship to junior engineers.
• Collaborate with engineers, product managers, and scientists to deliver high-impact solutions to complex business problems.

Skills

Python

Scala

Java

Go

Machine Learning

Distributed Systems

MLOps

Reinforcement Learning

Causal ML

Education

PhD/MS/Bachelor's in CS/ML/OR

Tools

Spark

Ray

Flink

Job description

Uber’s Dynamic Supply Pricing (DSP) team is building machine learning and algorithmic approaches to power real-time driver pricing at massive scale. In this Senior Machine Learning Engineer role, you’ll help design, develop, and productionize advanced ML models and pricing algorithms that support earnings opportunities for drivers while serving billions of trips.

What you’ll do

• Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems supporting billions of trips
• Develop novel pricing approaches for online marketplaces by combining machine learning with algorithmic game theory and optimization
• Partner with team leads to define the team’s technical direction and own implementation work
• Provide technical mentorship to junior engineers
• Collaborate with engineers, product managers, and scientists to deliver high-impact solutions to complex business problems

What you’ll need

• Ph.D., M.S., or Bachelor's degree in Computer Science, Machine Learning, or Operations Research (or equivalent technical background) with exceptional demonstrated impact
• 4+ years of experience developing and deploying machine learning models and optimization algorithms in large-scale production environments, including measurable business impact over multiple quarters and substantial technical contributions
• 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
• Experience spanning development, training, productionization, and monitoring of ML systems at scale, from offline pipelines to online serving and MLOps
• Deep understanding of modern ML algorithms (such as DNNs, multi-task models, and transformers) and mathematical optimization (such as LP and convex optimization)

Technologies

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

Bonus, equity, and benefits

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

Preferred qualifications

• Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• Experience leading complex technical projects and influencing the scope and output of others
• Track record translating ambiguous business problems into technical solutions and driving multi-functional projects
• Excellent communication skills for leading initiatives and collaborating with cross-functional partners
• Experience with reinforcement learning and causal machine learning

Location: San Francisco, CA (onsite)

Base salary: USD 202,000 - 224,000 per year

Office/remote work requirements: Unless approved for full remote work, employees must spend at least 50% of their time in-office.