Staff Software Engineer - Backend (Machine Learning) at Uber
San Francisco, CA
About the Job
About the RoleUber is looking for an outstanding engineer to join our team and drive innovation for Uber's E2E testing space.The Developer Platform team at Uber is consistently developing new and innovative ideas to enhance the developer’s experience and strengthen the quality of our apps
Quality and testing go hand in hand, and we took on a new and exciting challenge to change how we test our mobile,backend,web applications, with a focus on machine learning (ML)
Specifically, we are training models to test our applications just like real humans would.More details on our blogs
Your work will be instrumental in crafting a backend /ML infrastructure that supports scalability, reliability, and top-tier performance for quality.- Leverage Modern Technologies: Dive deep into the latest tools and frameworks
designing robust systems that can scale to meet growing demands, you'll be at the forefront of technological innovation.- Architect for the Future: Your system design skills will be put to the test as you create scalable architectures that not only meet today’s needs but are also prepared to evolve with our platform’s future growth
You'll ensure that our infrastructure is built to last, with the flexibility to adapt as we continue to innovate.Defining and driving ML/Backend solutions and build platform for end-to -end testing.- Mentorship and Leadership: As a senior member of the team, you will guide and mentor junior engineers, fostering a culture of continuous learning and improvement
Your insights will help shape the direction of our engineering practices and influence the next generation of backend developers.\-\-\-\- Basic Qualifications ----- A Bachelor's degree (or higher) in Computer Science or a related field, or equivalent practical experience.- 10+ years of experience in systems software engineering, with a solid understanding of computer architecture and computer science fundamentals.- Proficiency in one of the following programming languages: Java, Go, or Python.- Strong problem-solving skills with in-depth knowledge of algorithms, data structures, and complexity analysis.- Ability to work comfortably with ambiguity in a constantly evolving environment.\-\-\-\- Preferred Qualifications ----- Experience working on ML platforms or ML products.- Expertise in ML/AI/LLM (Machine Learning/Artificial Intelligence/Large Language Models).- Background in high-load distributed systems.##### Bonus Points:- Proven ability to maintain and enhance ML platforms- Familiarity with bleeding-edge tools in the Generative AI space.- Demonstrated ability to collaborate effectively with a globally distributed team, identify gaps in APIs, tooling, and infrastructure, and contribute to the development of effective solutions.For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 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 comp
You will also be eligible for various benefits
More details can be found at the following link [
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](
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.
Quality and testing go hand in hand, and we took on a new and exciting challenge to change how we test our mobile,backend,web applications, with a focus on machine learning (ML)
Specifically, we are training models to test our applications just like real humans would.More details on our blogs
https://www.uber.com/blog/generative-ai-for-high-quality-mobile-testing/https://www.uber.com/blog/shifting-e2e-testing-left/\-\-\-\-
What the Candidate Will Do ----- Innovate and Build: Collaborate with cross-functional teams to define and develop key features that enhance the developer work flows and qualityYour work will be instrumental in crafting a backend /ML infrastructure that supports scalability, reliability, and top-tier performance for quality.- Leverage Modern Technologies: Dive deep into the latest tools and frameworks
designing robust systems that can scale to meet growing demands, you'll be at the forefront of technological innovation.- Architect for the Future: Your system design skills will be put to the test as you create scalable architectures that not only meet today’s needs but are also prepared to evolve with our platform’s future growth
You'll ensure that our infrastructure is built to last, with the flexibility to adapt as we continue to innovate.Defining and driving ML/Backend solutions and build platform for end-to -end testing.- Mentorship and Leadership: As a senior member of the team, you will guide and mentor junior engineers, fostering a culture of continuous learning and improvement
Your insights will help shape the direction of our engineering practices and influence the next generation of backend developers.\-\-\-\- Basic Qualifications ----- A Bachelor's degree (or higher) in Computer Science or a related field, or equivalent practical experience.- 10+ years of experience in systems software engineering, with a solid understanding of computer architecture and computer science fundamentals.- Proficiency in one of the following programming languages: Java, Go, or Python.- Strong problem-solving skills with in-depth knowledge of algorithms, data structures, and complexity analysis.- Ability to work comfortably with ambiguity in a constantly evolving environment.\-\-\-\- Preferred Qualifications ----- Experience working on ML platforms or ML products.- Expertise in ML/AI/LLM (Machine Learning/Artificial Intelligence/Large Language Models).- Background in high-load distributed systems.##### Bonus Points:- Proven ability to maintain and enhance ML platforms- Familiarity with bleeding-edge tools in the Generative AI space.- Demonstrated ability to collaborate effectively with a globally distributed team, identify gaps in APIs, tooling, and infrastructure, and contribute to the development of effective solutions.For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 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 comp
You will also be eligible for various benefits
More details can be found at the following link [
https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits).Uber
is proud to be an Equal Opportunity/Affirmative Action employerAll 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](
https://forms.gle/aDWTk9k6xtMU25Y5A).Offices
continue to be central to collaboration and Uber’s cultural identityUnless 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.
