招聘
We're looking for PhD candidates to intern on the Data Storage team during summer 2026 (12 weeks). You will be embedded in our engineering team and work closely with other specialists, software developers, and product managers. As a PhD intern, you will work on an exciting yet bold problem in depth and independently, under the supervision of an experienced engineer on that team.
About the Team:
The Uber Data Storage team leverages various technologies hosting EB level of data to serve data analytics, ML, backup and other needs. We manage both structured and non structured data (especially multimodality data) for customers. In the era of AI, teams are working on many technically challenging problems to specifically serve our AI/ML customers performantly and efficiently.
What You'll Do:
- Drive exciting, ambitious, previously unsolved projects from end to end
- Thrive in ambiguous product requirements
- Collaborate with product managers, data scientists and machine learning engineers closely
- Make data driven decisions, with exceptional execution
- Be motivated to own projects and push them forward with independence
- Most importantly, have a passion to make Uber better for our customers
Basic Qualifications:
- Currently enrolled in a Ph.D. program studying distributed systems, machine learning, or a related engineering field
- Candidates must have at least one semester/quarter of their education left following the internship
Preferred Qualifications:
- Knowledge of underlying technical foundations of distributed systems, machine learning workflows, etc.
- Experience in one or more object-oriented languages, including C++, Java, Python, or Go.
- Ability to communicate effectively with both technical and business partners
- Experience in simplifying/converting business problems into technical problems
- Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation
- Experience presenting at industry recognized academic conferences and a good publishing record
- Experience with handling multimodality data in the industry
For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD**$67.00** per hour.
You will also be eligible for various 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.
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.
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关于Uber

Uber
PublicUber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.
10,001+
员工数
San Francisco
总部位置
$120B
企业估值
评价
3.7
10条评价
工作生活平衡
3.2
薪酬
4.0
企业文化
4.1
职业发展
3.4
管理层
2.8
68%
推荐给朋友
优点
Good compensation and pay
Flexible hours and schedule
Great team culture and colleagues
缺点
Long hours and tight deadlines
High pressure and stressful environment
Poor management and lack of support
薪资范围
15,354个数据点
Mid/L4
Mid/L4 · Data Analyst
3份报告
$209,300
年薪总额
基本工资
$161,000
股票
-
奖金
-
$203,580
$209,300
面试经验
5次面试
难度
3.0
/ 5
时长
14-28周
录用率
40%
体验
正面 80%
中性 20%
负面 0%
面试流程
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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