Staff Machine Learning Engineer - Pricing

Uber; New York (NY); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber’s Dynamic Supply Pricing team builds the machine learning and pricing algorithms that power real-time driver pricing at marketplace scale. In this Staff Machine Learning Engineering role, you will set technical direction over a 1+ year horizon and deliver end-to-end ML solutions that support distributed systems handling billions of trips.

Location: New York, NY onsite. You will own the technical roadmap, collaborate with cross-functional partners, and drive scalable ML models from

Responsibilities

• Own technical roadmap and strategy over the next 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
• Create novel pricing approaches for online marketplaces that combine machine learning, algorithmic game theory, and optimization to improve earnings opportunities for millions of drivers
• Partner with engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Skills

Ph.D./MS/Bachelor's in CS/ML/OR

6+ years ML production

Python

Scala

Java

Go

Spark

Ray

Flink

Microservices architectures

ML lifecycle

Pricing algorithms

Reinforcement learning

Education

PhD, MS, or Bachelor’s degree in Computer Science, Machine Learning, or Operations Research

Tools

Spark

Ray

Flink

Job description

Uber’s Dynamic Supply Pricing team builds the machine learning and pricing algorithms that power real-time driver pricing at marketplace scale. In this Staff Machine Learning Engineering role, you will set technical direction over a 1+ year horizon and deliver end-to-end ML solutions that support distributed systems handling billions of trips.

What you’ll do

• Own technical roadmap and strategy over the next 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
• Create novel pricing approaches for online marketplaces that combine machine learning, algorithmic game theory, and optimization to improve earnings opportunities for millions of drivers
• Partner with engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

What you’ll bring

• 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 of experience leading development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (for example, 1M+ predictions/sec or 100M+ users), with a track record of strong business impact across multiple quarters
• Proficiency in programming languages such as 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 across the ML lifecycle at scale, including development, training, productionization, and monitoring (offline pipelines to online serving and MLOps)
• Experience building and deploying pricing algorithms for multi-sided real-time marketplaces involving strategic agent behavior
• Deep understanding of modern ML algorithms (such as DNNs, multi-task models, and transformers) and mathematical optimization (such as multi-objective, LP, and convex optimization)
• Preferred: reinforcement learning and causal machine learning proficiency

Technologies

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

Compensation and location

Location: New York, NY (onsite)

• Salary: USD 232,000 - 258,000 per year
• Base salary range (NYC): USD $232,000 per year - USD $258,000 per year

Bonus, equity, and benefits

• 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

Work model

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