Overview
On Site
USD 185,000.00 - 205,500.00 per year
Full Time
Skills
Forecasting
Dynamics
Leadership
IT management
Design
Mentorship
Computer science
TensorFlow
PyTorch
JAX
scikit-learn
FOCUS
Machine Learning (ML)
Deep learning
Statistics
Optimization
Online learning
Agile
Communication
Law
Legal
Collaboration
Job Details
About the Role
The Earner Incentive team at Marketplace builds ML solutions for incentives to improve marketplace balance and efficiency. The team builds machine learning systems to solve critical ML problems in Marketplace such as forecasting undersupply geo and times, optimizing incentive levers to influence marketplace dynamics, and understanding earner behaviors and preferences for targeting / personalization.
We are looking for an experienced ML engineer to lead the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems. You will build ML solutions to improve Uber's earner incentive products and improve marketplace balance and efficiency. You will also lead ML engineers, provide technical leadership and directions for the team.
What You Will Do
For Sunnyvale, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 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 .
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 .
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.
The Earner Incentive team at Marketplace builds ML solutions for incentives to improve marketplace balance and efficiency. The team builds machine learning systems to solve critical ML problems in Marketplace such as forecasting undersupply geo and times, optimizing incentive levers to influence marketplace dynamics, and understanding earner behaviors and preferences for targeting / personalization.
We are looking for an experienced ML engineer to lead the design, development, optimization, and productization of machine learning (ML) solutions and systems that are used to solve strategically important or vaguely defined problems. You will build ML solutions to improve Uber's earner incentive products and improve marketplace balance and efficiency. You will also lead ML engineers, provide technical leadership and directions for the team.
What You Will Do
- Design, develop, and productionize machine learning (ML) solutions with optimization engines.
- Productionize and deploy these models for real-world application.
- Review code and designs of teammates, providing constructive feedback.
- Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.
- Mentor junior engineers.
- Bachelors (or higher) in Computer Science, Statistics, or a related field.
- Experience with ML packages such as Tensorflow, PyTorch, JAX, Scikit-Learn, etc.
- 5+ years of experience in industry with a strong focus on machine learning and optimization.
- Experience in modern deep learning architectures and probabilistic models.
- Solid understanding of statistical analysis and feature engineering techniques.
- Experience in optimization (RL / Bayes / Bandits) and online learning.
- Experience working in a fast-paced, agile environment.
- Excellent communication and collaboration skills.
- Ability to work independently and take ownership of projects.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 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 .
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 .
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.