About the Role
As a Senior Staff Software Engineer at Uber, you will play a pivotal role in designing and building the next generation of our driver algorithmic pricing systems. You will lead initiatives that impact millions of drivers globally, enhancing their experience and optimizing pricing strategies through cutting-edge technology.
Your work will span across infrastructure, backend development, platform integration, analytics/experiment infrastructure, and developer/testing frameworks. By joining our dynamic team, you will contribute to the improvements with developer velocity, scalability, reliability, and efficiency of our pricing algorithms, ensuring we continue to innovate and deliver exceptional results.
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---- What You Will Do ----
- Lead the design, development, and deployment of scalable and reliable backend systems for driver algorithmic pricing.
- Collaborate with cross-functional teams including data scientists, product managers, and other engineering teams to deliver end-to-end solutions.
- Develop and enhance our platform infrastructure to support advanced analytics and experimentation capabilities.
- Implement robust developer and testing infrastructure to streamline development workflows and ensure high-quality code.
- Drive continuous improvement in system architecture and operational excellence, with a focus on performance, scalability, and maintainability.
- Mentor and provide technical guidance to junior engineers, fostering a culture of innovation and excellence within the team.
- Stay current with the latest technologies and industry trends, evaluating and integrating new tools and methodologies as appropriate.
---- 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, C++, Python, or Go.
- Strong experience with distributed systems and microservices architecture
- Proven track record in designing and implementing large-scale, high-performance systems.
- Experience with data analytics and experimental design in an engineering context.
- Excellent problem-solving skills and the ability to think critically and creatively.
---- Preferred Qualifications ----
- Master's or Ph.D. in Computer Science, Engineering, or a related field.
- 10+ years of experience in software engineering, particularly in building and maintaining large-scale pricing or recommendation systems.
- Deep understanding of algorithmic pricing models and techniques.
- Experience with machine learning frameworks and tools.
- Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
- Strong background in data analytics tools such as Apache Spark, Hive, or similar.
- Familiarity with CI/CD pipelines and testing frameworks.
- Demonstrated leadership skills, with experience in mentoring and guiding junior engineers.
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.