Overview
On Site
USD 223,000.00 - 248,000.00 per year
Full Time
Skills
Pricing
IT Management
Computer Science
Artificial Intelligence
Statistics
Python
C++
Java
Machine Learning (ML)
Deep Learning
TensorFlow
PyTorch
Keras
Modeling
Research
Communication
Law
Legal
Collaboration
Job Details
About the Role
We are looking for a Staff ML Engineer to join our Delivery Pricing & Incentives team at Uber. In this role, you will design and productionize end-to-end ML solutions to tackle strategically important challenges in Uber's multi-sided marketplace, impacting the top-line and bottom-line of the business. You will provide ML technical leadership, identify gaps/opportunities, and influence the org's direction of ML-powered product innovations.
What You Will Do
- Partner with cross-functional teams to enhance consumer-facing products
- Provide ML technical leadership and identify gaps/opportunities to optimize business outcomes
- Design and productionize end-to-end ML solutions to tackle strategically important challenges in Uber's multi-sided marketplace
Basic Qualifications
- Bachelor's (or higher) degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 5+ years of experience in developing and operating machine learning solutions in production environment
- Strong programming skills in languages such as Python, C++, or Java
Preferred Qualifications
- 3+ years of experience in developing and operating machine learning solutions in production environment
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Strong knowledge in personalization / economic modeling / causal inference and familiarity with modern research in the field is highly valued
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams
For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.
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.
We are looking for a Staff ML Engineer to join our Delivery Pricing & Incentives team at Uber. In this role, you will design and productionize end-to-end ML solutions to tackle strategically important challenges in Uber's multi-sided marketplace, impacting the top-line and bottom-line of the business. You will provide ML technical leadership, identify gaps/opportunities, and influence the org's direction of ML-powered product innovations.
What You Will Do
- Partner with cross-functional teams to enhance consumer-facing products
- Provide ML technical leadership and identify gaps/opportunities to optimize business outcomes
- Design and productionize end-to-end ML solutions to tackle strategically important challenges in Uber's multi-sided marketplace
Basic Qualifications
- Bachelor's (or higher) degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 5+ years of experience in developing and operating machine learning solutions in production environment
- Strong programming skills in languages such as Python, C++, or Java
Preferred Qualifications
- 3+ years of experience in developing and operating machine learning solutions in production environment
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Strong knowledge in personalization / economic modeling / causal inference and familiarity with modern research in the field is highly valued
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams
For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.
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.