Overview
On Site
USD 257,000.00 - 285,500.00 per year
Full Time
Skills
Data Analysis
Operational Efficiency
Art
Technical Direction
IT Management
Algorithms
Systems Design
Communication
Python
Java
C++
Computer Science
Artificial Intelligence
Statistics
Machine Learning (ML)
Deep Learning
Generative Artificial Intelligence (AI)
Research
Law
Legal
Collaboration
Job Details
About the Role
We are looking for a Sr Staff Machine Learning Engineer to join the Eats Search Ranking Team. You will play a critical tech lead role in improving relevance and ranking for search results across all Uber Eats surfaces. Your work will have significant impact on the search experience for millions of Uber Eats users worldwide.. You will leverage your expertise in data analysis, machine learning, and Engineering to drive insights and optimize search algorithms, ultimately improving user satisfaction and operational efficiency.
What the Candidate Will Do:
- Lead the team in design, development, and deployment ofstate-of-the-art machine learning models and algorithms to solve business problems and improve product performance.
- Collaborate with applied/data scientists, software engineers, and product managers to understand requirements, define project goals, and deliver high-quality solutions.
- Set long term technical direction for the team and uphold high engineering and ML quality bar
- Provide technical leadership and direction to fellow software & ML engineers in the team
- Identify new business opportunities to solve problems with the right technologies, and stay up-to-date with the latest advancements in machine learning techniques and technologies.
Basic Qualifications:
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 9+ years of experience in developing and deploying machine learning models and algorithms in production environments
- Deep understanding of machine learning algorithms and ranking / recommendation systems, and strong system design skills
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams
- Strong programming skills in languages such as Python, Java, or C++
Preferred Qualifications:
- Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- Experience directly tech leading a 10+ machine learning team focusing on large scale search and ranking applications.
- Familiarity with latest development in the field of deep learning, LLM, generative AI, recommendation system and related fields. Track record of applied research is a plus.
For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 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 [](;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 Sr Staff Machine Learning Engineer to join the Eats Search Ranking Team. You will play a critical tech lead role in improving relevance and ranking for search results across all Uber Eats surfaces. Your work will have significant impact on the search experience for millions of Uber Eats users worldwide.. You will leverage your expertise in data analysis, machine learning, and Engineering to drive insights and optimize search algorithms, ultimately improving user satisfaction and operational efficiency.
What the Candidate Will Do:
- Lead the team in design, development, and deployment ofstate-of-the-art machine learning models and algorithms to solve business problems and improve product performance.
- Collaborate with applied/data scientists, software engineers, and product managers to understand requirements, define project goals, and deliver high-quality solutions.
- Set long term technical direction for the team and uphold high engineering and ML quality bar
- Provide technical leadership and direction to fellow software & ML engineers in the team
- Identify new business opportunities to solve problems with the right technologies, and stay up-to-date with the latest advancements in machine learning techniques and technologies.
Basic Qualifications:
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 9+ years of experience in developing and deploying machine learning models and algorithms in production environments
- Deep understanding of machine learning algorithms and ranking / recommendation systems, and strong system design skills
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams
- Strong programming skills in languages such as Python, Java, or C++
Preferred Qualifications:
- Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- Experience directly tech leading a 10+ machine learning team focusing on large scale search and ranking applications.
- Familiarity with latest development in the field of deep learning, LLM, generative AI, recommendation system and related fields. Track record of applied research is a plus.
For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 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 [](;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.