About the Role
Uber is on the lookout for top-notch software engineers to join our Machine Learning Platform team. This role involves building and managing robust distributed systems, and solving infrastructure challenges to empower Uber’s product engineering and data science teams with the latest technologies in large scale Artificial Intelligence.The Machine Learning Platform team works on software and services that democratize and empower teams across Uber to use the technology. You will be part of a team of strong software and systems engineers executing in an exciting, dynamic environment. The Machine Learning Platform team is part of Michelangelo. For more information on the Michelangelo team as a whole, please visit our recent blog posts:
- From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey: Uber’s Machine Learning Platform: https://www.uber.com/blog/from-predictive-to-generative-ai/
- Scaling AI/ML Infrastructure at Uber: https://uber.com/blog/scaling-ai-ml-infrastructure-at-uber/
What the Candidate Will Do ----
- Design and deliver software and tools as part of our state-of-the-art Machine Learning platform
- Systems architecture design, including management of upstream and downstream dependencies
- Provide technical leadership, influence and partner with fellow engineers to architect, design and build infrastructure that can stand the test of scale and availability, while reducing operational overhead
- Drive efficiencies in systems and processes through automation: capacity planning, configuration management, performance tuning, monitoring and root cause analysis
- Participate in periodic on-call rotations and be available for critical issues
- Collaborate with platform, product and security engineering teams, and enable successful use of infrastructure and foundational services
---- Basic Qualifications ----
- BS or MS in Computer Science or a related technical field, or equivalent experience
- Sound understanding of computer architecture and CS fundamentals
- Proficient in one of the following programming languages: Java, Go, Python
- Good working knowledge of networking, Linux, Docker, databases, Hadoop, Hive, Spark, Ray
---- Preferred Qualifications ----
- 3+ years of experience of systems software engineering
- Some experience designing UI in JavaScript
- Good understanding or experience with Protobuff and experience with Kubernetes
- Experience building and managing distributed systems and high-throughput services
- Systematic problem solving approach and knowledge of algorithms, data structures and complexity analysis
- Grit, drive and a strong feeling of ownership coupled with collaboration and leadership
- Power-user Linux knowledge and willingness to explore Linux internals
- Designing and developing backend services at scale
- Good understanding of databases
For Sunnyvale, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 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.
