About the Role
As a Senior Staff Software Engineer at Uber, you will play a critical role in shaping the future of our driver algorithmic pricing systems. This role is pivotal in ensuring our pricing models are robust, scalable, and efficient, contributing to an optimized experience for our drivers and riders.
You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge infrastructure and backend systems. Your work will involve a combination of backend engineering, platform development, analytics, experimentation infrastructure, developer/testing infrastructure, machine learning, and optimization.
We are looking for a strong generalist who can adapt to various technical challenges and bring innovative solutions to our dynamic team.
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---- What the Candidate Will Do ----
- Design, develop, and maintain the infrastructure and backend systems for Uber's driver algorithmic pricing.
- Implement scalable and efficient algorithms to improve pricing accuracy and performance.
- Collaborate with data scientists, product managers, and other engineers to integrate machine learning models and optimization techniques.
- Build and maintain experimentation and analytics infrastructure to support data-driven decision-making.
- Develop and enhance developer and testing infrastructure to ensure high-quality code and rapid iteration.
- Monitor and optimize system performance, reliability, and scalability.
- Mentor junior engineers and contribute to the overall technical growth of the team.
- Stay up-to-date with the latest industry trends and technologies to ensure Uber's systems remain at the forefront of innovation.
---- Basic Qualifications ----
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 8+ years of experience in software engineering with a focus on backend and infrastructure development.
- Proficiency in one or more programming languages such as Java, Python, or Go.
- Experience with distributed systems, microservices architecture, and large-scale system design.
- Strong analytical and problem-solving skills.
- Solid understanding of data structures, algorithms, and software design principles.
---- Preferred Qualifications ----
- Master's or PhD in Computer Science, Engineering, or a related field.
- 10+ years of experience in software engineering.
- Experience in developing pricing algorithms or similar systems.
- Knowledge of machine learning and optimization techniques.
- Experience with analytics and experimentation infrastructure.
- Knowledge of DevOps practices and tools for CI/CD.
- Strong communication skills with the ability to work effectively in a team environment.
- Previous experience in a high-growth tech company or startup environment.
For San Francisco, CA-based roles: The base salary range for this role is USD$252,000 per year - USD$280,000 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 https://www.uber.com/careers/benefits.
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.
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.