**About the Role**

This is an exciting opportunity to work at the intersection of both Data and AI. Data Storage team is managing Storage solutions for both structured and non structured data and we are transitioning into a Cloud based Storage solution provider. With much ease and modernization from Cloud, challenges also come from lifted latency of data loading, cumbersome metadata management and increasing cost. We would also like to better serve our AI/ML customers to provide more handy sets of APIs, better one-stop solution to leverage GPU cross region and cross vendor. The team is building several new solutions to catch up with growing needs.

**What the Candidate Will Need / Bonus Points**

1. Work in complex Data Storage related components including Blob Storage Metadata service, Catalog and Cloud Object Stores etc
2. Deep dive into specific technologies, understanding related source code and configuration. Fine-tune performance of these systems to improve overall performance and reliability. Find and build solutions to innovate the Cloud usage, striking the balance of performance and efficiency
3. Work with Uber internal AI/ML teams to design and implement solutions. Turn high level technical strategies into production systems.
4. Have a broad understanding of related systems in the industry, follow state-of-art industry solutions with a good sense of adoption in Uber
5. Lead other team members to solve technical problems and deliver production mature solutions

\-\-\-\- Basic Qualifications ----

1. 10+ years of Software Engineering Industry experience
2. Strong engineering skills, including reading open source code, implementing solutions and performance tuning.
3. Experience building large scale distributed software systems.
4. Industry experience in big data, Cloud based storage solution or related systems, preferably operating mission-critical systems to solve large-scale real-world problems; programming languages such as Python, Java, Go, C++ and Rust
5. Industry experience with machine learning systems, ex. Ray or Pytorch
6. Experience working with a team to deliver large, complex and reliable software with strict SLA requirements

\-\-\-\- Preferred Qualifications ----

1. MS / PhD in Computer Science or related field.
2. Committer/Contributor to AI/ML or big data frameworks (e.g. Pytorch, Ray, Iceberg, Lance, Gravitino, Polaris)
3. Experience developing with solutions leveraging Cloud Object Store like S3/GCS/Azure/OCI.
4. Experience developing with supporting business critical systems with 99.9+ availability
5. Deep understanding of modern large scale of AI infrastructure

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For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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](https://www.uber.com/careers/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](https://forms.gle/aDWTk9k6xtMU25Y5A).

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.