Pricing Modeling

Pricing Modeling Data Jobs

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1d ago

Staff Machine Learning Engineer - Pricing

Uber New York, NY

New York, NY

1d ago

$232k - $258k/yr Full time Big Data Data Pipeline Data Processing

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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

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2d ago

Staff Machine Learning Engineer - Pricing

Uber Sunnyvale, CA

Sunnyvale, CA

2d ago

$232k - $258k/yr Full time Artificial Intelligence Data Pipeline Data Platform

Apply Now

Job Description

Uber’s Dynamic Supply Pricing team is seeking a Staff Machine Learning Engineer to lead advanced ML and pricing model work for real-time driver pricing.

Responsibilities

Own technical strategy and roadmap planning over a 1+ year horizon
Lead implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence
Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems handling billions of trips
Build novel pricing approaches for online marketplaces using machine learning, algorithmic game theory, and optimization
Collaborate 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 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 (example scale: 1M+ predictions/sec or 100M+ users)
Demonstrated track record of delivering outstanding business impact over multiple quarters
Programming proficiency in Python, Scala, Java, or Go
Experience with large-scale data systems (Spark, Ray), real-time processing (Flink), and microservices architectures
Proficiency in building, training, productionizing, and monitoring ML solutions at scale, from offline pipelines to online serving and MLOps
Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces involving strategic agent behavior
Strong foundation in modern ML algorithms (DNNs, multi-task models, transformers) and mathematical optimization (multi-objective, LP, convex optimization)

Preferred Qualifications

Experience owning multi-year technical strategies and cross-team platform architecture
Demonstrated ability to translate complex business problems into technical solutions and drive multi-functional, multi-team projects
Excellent communication skills to lead initiatives across multiple product areas
Proficiency in reinforcement learning and causal machine learning

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
May be offered an equity award and other types of comp
Eligible for a 401(k) plan
Eligible for various benefits

Location and Work Expectations

Sunnyvale, CA (onsite)
Unless approved for full remote work, employees must spend at least 50% of their time in-office
Some roles may require full-time in-office presence (e.g., greenlight hubs)
Ask your Recruiter for details about this role’s requirements

View full job page →

Pricing Modeling Data Jobs

Staff Machine Learning Engineer - Pricing

Staff Machine Learning Engineer - Pricing

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