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Staff Machine Learning Engineer - Marketplace Pricing

Uber

Software and Technology Jobs

Staff Machine Learning Engineer - Marketplace Pricing

full-timePosted: Jul 16, 2025

Job Description

Staff Machine Learning Engineer - Marketplace Pricing

šŸ“‹ Job Overview

Uber's Dynamic Supply Pricing team seeks a Staff Machine Learning Engineer to lead the development of ML models and pricing algorithms for real-time driver pricing. The role involves working on cutting-edge marketplace ML problems and multi-objective optimizations, offering significant career growth and mentorship opportunities.

šŸ“ Location: New York, New York, United States

šŸ¢ Department: Engineering

šŸ“„ Full Description

**About the Role**

Uber’s Marketplace is at the heart of Uber’s business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.

We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team’s technical direction and solve some of Uber’s most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

**What You Will Do**

- Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

**Basic 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
- 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

**Preferred Qualifications**

- Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing 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 to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
- Proficiency in reinforcement learning and causal machine learning

For New York, NY-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits).

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

šŸŽÆ Key Responsibilities

  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

āœ… Required 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
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

šŸ› ļø Required Skills

  • Machine Learning
  • Optimization Algorithms
  • Programming (Python, Scala, Java, or Go)
  • Large-scale Data Systems (Spark, Ray)
  • Real-time Processing (Flink)
  • Microservices Architectures
  • MLOps
  • Pricing Algorithms
  • Modern ML Algorithms (DNNs, multi-task models, transformers)
  • Mathematical Optimization (multi-objective, LP, convex optimization)

šŸŽ Benefits

  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible for various benefits (details at https://www.uber.com/careers/benefits)

Locations

  • New York, New York, United States

Salary

223,000 - 248,000 USD / yearly

Estimated Salary Rangemedium confidence

150,000 - 220,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Machine Learningintermediate
  • Optimization Algorithmsintermediate
  • Programming (Python, Scala, Java, or Go)intermediate
  • Large-scale Data Systems (Spark, Ray)intermediate
  • Real-time Processing (Flink)intermediate
  • Microservices Architecturesintermediate
  • MLOpsintermediate
  • Pricing Algorithmsintermediate
  • Modern ML Algorithms (DNNs, multi-task models, transformers)intermediate
  • Mathematical Optimization (multi-objective, LP, convex optimization)intermediate

Required 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 (experience)
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters (experience)
  • Proficiency in programming languages such as Python, Scala, Java, or Go (experience)
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures (experience)
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps (experience)
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior (experience)
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization) (experience)

Preferred Qualifications

  • Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others (experience)
  • Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams (experience)
  • Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams (experience)
  • Proficiency in reinforcement learning and causal machine learning (experience)

Responsibilities

  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Benefits

  • general: Eligible to participate in Uber's bonus program
  • general: May be offered an equity award & other types of comp
  • general: Eligible for various benefits (details at https://www.uber.com/careers/benefits)

Target Your Resume for "Staff Machine Learning Engineer - Marketplace Pricing" , Uber

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Uber logo

Staff Machine Learning Engineer - Marketplace Pricing

Uber

Software and Technology Jobs

Staff Machine Learning Engineer - Marketplace Pricing

full-timePosted: Jul 16, 2025

Job Description

Staff Machine Learning Engineer - Marketplace Pricing

šŸ“‹ Job Overview

Uber's Dynamic Supply Pricing team seeks a Staff Machine Learning Engineer to lead the development of ML models and pricing algorithms for real-time driver pricing. The role involves working on cutting-edge marketplace ML problems and multi-objective optimizations, offering significant career growth and mentorship opportunities.

šŸ“ Location: New York, New York, United States

šŸ¢ Department: Engineering

šŸ“„ Full Description

**About the Role**

Uber’s Marketplace is at the heart of Uber’s business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.

We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team’s technical direction and solve some of Uber’s most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

**What You Will Do**

- Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

**Basic 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
- 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

**Preferred Qualifications**

- Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing 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 to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams
- Proficiency in reinforcement learning and causal machine learning

For New York, NY-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits).

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

šŸŽÆ Key Responsibilities

  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

āœ… Required 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
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

šŸ› ļø Required Skills

  • Machine Learning
  • Optimization Algorithms
  • Programming (Python, Scala, Java, or Go)
  • Large-scale Data Systems (Spark, Ray)
  • Real-time Processing (Flink)
  • Microservices Architectures
  • MLOps
  • Pricing Algorithms
  • Modern ML Algorithms (DNNs, multi-task models, transformers)
  • Mathematical Optimization (multi-objective, LP, convex optimization)

šŸŽ Benefits

  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible for various benefits (details at https://www.uber.com/careers/benefits)

Locations

  • New York, New York, United States

Salary

223,000 - 248,000 USD / yearly

Estimated Salary Rangemedium confidence

150,000 - 220,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Machine Learningintermediate
  • Optimization Algorithmsintermediate
  • Programming (Python, Scala, Java, or Go)intermediate
  • Large-scale Data Systems (Spark, Ray)intermediate
  • Real-time Processing (Flink)intermediate
  • Microservices Architecturesintermediate
  • MLOpsintermediate
  • Pricing Algorithmsintermediate
  • Modern ML Algorithms (DNNs, multi-task models, transformers)intermediate
  • Mathematical Optimization (multi-objective, LP, convex optimization)intermediate

Required 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 (experience)
  • 6+ years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M+ predictions/sec or 100M+ users). Track record of delivering outstanding business impact over multiple quarters (experience)
  • Proficiency in programming languages such as Python, Scala, Java, or Go (experience)
  • Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures (experience)
  • Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps (experience)
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior (experience)
  • Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization) (experience)

Preferred Qualifications

  • Experience developing multi-year technical strategies and cross-team platform architecture, and proficiency owning technical roadmap and leading complex technical projects while substantially influencing the scope and output of others (experience)
  • Track record of translating complex business problems into technical solutions and driving multi-functional projects across multiple teams (experience)
  • Excellent communication skills to lead initiatives across multiple product areas and collaborate effectively with cross-functional teams (experience)
  • Proficiency in reinforcement learning and causal machine learning (experience)

Responsibilities

  • Drive technical strategy and roadmap ownership over a 1+ year horizon and own the implementation, 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 combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Benefits

  • general: Eligible to participate in Uber's bonus program
  • general: May be offered an equity award & other types of comp
  • general: Eligible for various benefits (details at https://www.uber.com/careers/benefits)

Target Your Resume for "Staff Machine Learning Engineer - Marketplace Pricing" , Uber

Get personalized recommendations to optimize your resume specifically for Staff Machine Learning Engineer - Marketplace Pricing. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Staff Machine Learning Engineer - Marketplace Pricing" , Uber

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

UberNew YorkUnited StatesEngineeringEngineering

Answer 10 quick questions to check your fit for Staff Machine Learning Engineer - Marketplace Pricing @ Uber.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.