Senior Machine Learning Engineer, Rider (Multiple Teams)
Uber
San Francisco, California
Posted 6 days ago
Qualifications
Education
Bachelor's degree in Computer Science, Engineering, Mathematics or related field.
Responsibilities
Primary Duties
- Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising.
- Provide technical leadership to a passionate, experienced, and diverse engineering team.
- Raise the bar of ML engineering by improving best practices.
- Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions.
Experience Requirements
Required
3+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation.
3 years of experience
Required Skills
Technical Skills
ML methodologiesML frameworks (e.g. Tensorflow, Pytorch, or JAX)complex data pipelinesprogramming languages such as Python, Spark SQL, Presto, Java, Go
Full Job Description
Senior Machine Learning Engineer, Rider (Multiple Teams)
Machine Learning, Engineering
Seattle, Washington | San Francisco, California | Sunnyvale, California
Full Time
The Aura team powers a real-time ML engine personalizing the booking experience for millions of riders. By predicting preferences and recommending Rides products, it drives conversion using hundreds of marketplace and historical features and generates billions in incremental revenue. We stay at the forefront of innovation by employing cutting-edge techniques like multi-task learning, sequence modeling, and transformers, applying statistical and operations research principles globally. Sitting at the center of the conversion funnel, we collaborate closely with scientists and product managers at the intersection of economics and infrastructure.
The Rider Intelligence team owns various machine learning models that power the personalization of the Uber app. As a software engineer, you will work with Machine Learning Engineers (MLEs) to deploy and enhance these models such as sequential recommendation systems to improve the user experience and business metrics. We are looking for software engineers who have a strong foundation in distributed systems and are eager to learn the ML/data science domain.
What You'll Do
Basic Qualifications
Preferred Qualifications
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 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 compensation. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/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.
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.
Machine Learning, Engineering
Seattle, Washington | San Francisco, California | Sunnyvale, California
Full Time
The Aura team powers a real-time ML engine personalizing the booking experience for millions of riders. By predicting preferences and recommending Rides products, it drives conversion using hundreds of marketplace and historical features and generates billions in incremental revenue. We stay at the forefront of innovation by employing cutting-edge techniques like multi-task learning, sequence modeling, and transformers, applying statistical and operations research principles globally. Sitting at the center of the conversion funnel, we collaborate closely with scientists and product managers at the intersection of economics and infrastructure.
The Rider Intelligence team owns various machine learning models that power the personalization of the Uber app. As a software engineer, you will work with Machine Learning Engineers (MLEs) to deploy and enhance these models such as sequential recommendation systems to improve the user experience and business metrics. We are looking for software engineers who have a strong foundation in distributed systems and are eager to learn the ML/data science domain.
What You'll Do
- Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising: help riders find and complete rides with the right products, understanding their ride context and modeling their intent while attending to Uber's business goals, marketplace conditions and efficiencies.
- Provide technical leadership to a passionate, experienced, and diverse engineering team. Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions. Classification, regression, and multi-task learning are in our toolbox.
- Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough & precise monitoring, and applying model debugging & interpretation techniques.
- Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions.
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics or related field.
- 3+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation.
- Strong problem-solving skills, with expertise in ML methodologies.
- Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems).
- Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Java, Go.
Preferred Qualifications
- 5+ years of experience in software engineering specializing in applied ML methods.
- Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods.
- Innate truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions.
- Experience with deep-learning techniques, having worked with embeddings and transformer architectures.
- 1+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team's strategies.
- Passionate about helping junior members grow by inspiring and mentoring engineers.
- Resilience, determination, ownership mindset.
- PhD degree in Computer Science, Engineering, Mathematics or related field.
For San Francisco, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 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 compensation. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/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.
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.
How to Apply
$138
/ hour
Uber pays $138 for Software Engineer in San Francisco, California, with most salaries ranging from $104 to $183. Pay can vary based on role, experience, and local cost of living.
Median
$138
Low
$104
High
$183
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Figures represent approximate ranges and may vary based on experience, location, and other factors. For the most accurate information, please consult the employer directly. Contact us to suggest updates to this information.





