U
Senior Machine Learning Engineer - Marketplace Earner Incentives
Salary undisclosed
Checking job availability...
Original
Simplified
About the Role
In this role, with the Marketplace Earner Incentives team, you will contribute to building the next generation of models and systems aimed at addressing undersupply issues in the marketplace by effectively incentivizing drivers. You'll have the opportunity to make a meaningful impact on the lives of riders and drivers at Uber scale through end-to-end ownership of high-impact projects.
If you're excited by complex, real-world challenges-like motivating drivers in highly competitive markets with incomplete information-this is the space for you. You'll thrive by diving into problems, formulating and testing hypotheses, rapidly identifying simple solutions, and iterating quickly to drive continuous improvement.
\\-\\-\\-\\- What You Will Do ----
- Work with product, science, engineering, and operations to identify, build, test, and deploy product solutions for the team.
- Build new models, identify new signals, scale them up to a global scale
\\-\\-\\-\\- Basic Qualifications ----
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience collaborating cross-functionally with product and other engineering roles.
- Driven and curious.
- Either 3+ years of experience building production machine learning systems at scale and a Masters or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, Economics, or a related field.
- 2+ years of experience building production machine learning systems at scale and a PhD or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, or a related field.
\\-\\-\\-\\- Preferred Qualifications ----
- Exceptional technical communication skills.
- Experience writing custom models in Pytorch or Tensorflow/Keras.
- Experience with working with large scale data processing systems like (Py)Spark and Presto/Trino.
- Experience training models at scale.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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 [](;br>
Uber is proud to be an Equal Opportunity/Affirmative Action 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](;br>
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.
In this role, with the Marketplace Earner Incentives team, you will contribute to building the next generation of models and systems aimed at addressing undersupply issues in the marketplace by effectively incentivizing drivers. You'll have the opportunity to make a meaningful impact on the lives of riders and drivers at Uber scale through end-to-end ownership of high-impact projects.
If you're excited by complex, real-world challenges-like motivating drivers in highly competitive markets with incomplete information-this is the space for you. You'll thrive by diving into problems, formulating and testing hypotheses, rapidly identifying simple solutions, and iterating quickly to drive continuous improvement.
\\-\\-\\-\\- What You Will Do ----
- Work with product, science, engineering, and operations to identify, build, test, and deploy product solutions for the team.
- Build new models, identify new signals, scale them up to a global scale
\\-\\-\\-\\- Basic Qualifications ----
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience collaborating cross-functionally with product and other engineering roles.
- Driven and curious.
- Either 3+ years of experience building production machine learning systems at scale and a Masters or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, Economics, or a related field.
- 2+ years of experience building production machine learning systems at scale and a PhD or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, or a related field.
\\-\\-\\-\\- Preferred Qualifications ----
- Exceptional technical communication skills.
- Experience writing custom models in Pytorch or Tensorflow/Keras.
- Experience with working with large scale data processing systems like (Py)Spark and Presto/Trino.
- Experience training models at scale.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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 [](;br>
Uber is proud to be an Equal Opportunity/Affirmative Action 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](;br>
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job About the Role
In this role, with the Marketplace Earner Incentives team, you will contribute to building the next generation of models and systems aimed at addressing undersupply issues in the marketplace by effectively incentivizing drivers. You'll have the opportunity to make a meaningful impact on the lives of riders and drivers at Uber scale through end-to-end ownership of high-impact projects.
If you're excited by complex, real-world challenges-like motivating drivers in highly competitive markets with incomplete information-this is the space for you. You'll thrive by diving into problems, formulating and testing hypotheses, rapidly identifying simple solutions, and iterating quickly to drive continuous improvement.
\\-\\-\\-\\- What You Will Do ----
- Work with product, science, engineering, and operations to identify, build, test, and deploy product solutions for the team.
- Build new models, identify new signals, scale them up to a global scale
\\-\\-\\-\\- Basic Qualifications ----
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience collaborating cross-functionally with product and other engineering roles.
- Driven and curious.
- Either 3+ years of experience building production machine learning systems at scale and a Masters or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, Economics, or a related field.
- 2+ years of experience building production machine learning systems at scale and a PhD or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, or a related field.
\\-\\-\\-\\- Preferred Qualifications ----
- Exceptional technical communication skills.
- Experience writing custom models in Pytorch or Tensorflow/Keras.
- Experience with working with large scale data processing systems like (Py)Spark and Presto/Trino.
- Experience training models at scale.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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 [](;br>
Uber is proud to be an Equal Opportunity/Affirmative Action 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](;br>
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.
In this role, with the Marketplace Earner Incentives team, you will contribute to building the next generation of models and systems aimed at addressing undersupply issues in the marketplace by effectively incentivizing drivers. You'll have the opportunity to make a meaningful impact on the lives of riders and drivers at Uber scale through end-to-end ownership of high-impact projects.
If you're excited by complex, real-world challenges-like motivating drivers in highly competitive markets with incomplete information-this is the space for you. You'll thrive by diving into problems, formulating and testing hypotheses, rapidly identifying simple solutions, and iterating quickly to drive continuous improvement.
\\-\\-\\-\\- What You Will Do ----
- Work with product, science, engineering, and operations to identify, build, test, and deploy product solutions for the team.
- Build new models, identify new signals, scale them up to a global scale
\\-\\-\\-\\- Basic Qualifications ----
- Comfortable programming in at least one major language such as Python (preferred), Scala, Go,...
- Experience collaborating cross-functionally with product and other engineering roles.
- Driven and curious.
- Either 3+ years of experience building production machine learning systems at scale and a Masters or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, Economics, or a related field.
- 2+ years of experience building production machine learning systems at scale and a PhD or equivalent in Machine Learning, Computer Science, Mathematics, Statistics, or a related field.
\\-\\-\\-\\- Preferred Qualifications ----
- Exceptional technical communication skills.
- Experience writing custom models in Pytorch or Tensorflow/Keras.
- Experience with working with large scale data processing systems like (Py)Spark and Presto/Trino.
- Experience training models at scale.
For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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 [](;br>
Uber is proud to be an Equal Opportunity/Affirmative Action 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](;br>
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job