招聘
About the Role
We are seeking a strong and passionate staff software engineer with experience in building distributed and scalable, secure systems. You will be responsible for creating scalable, reliable, manageable solutions that deliver on building platforms at Uber. You will be owning customer facing and agent facing support experience of millions of customers.
Your responsibility will include identifying required changes across Uber's engineering ecosystem, collaborating with engineering teams, driving consensus, implementing extensible, maintainable changes required to build state-of-the-art support experiences.
We are looking for someone who has passion for designing and driving large projects from inception to production. The right person will work with stakeholders, product managers, scientists, partner engineering teams to gather requirements and translate them into a platform feature. Must be a great communicator, team player, and a technical powerhouse.
-- Basic Qualifications ----
- 9+ years of experience in software development.
- Experience with:
- Scalable system architecture design
- Production-quality services, deployment, monitoring, and reliability.
- Micro service designs, g
RPC or REST API development:
- Ability to decompose complex business problems into clean, extensible, performant services and systems
- Logging, monitoring, performance troubleshooting and tuning experience
- Excellent problem-solving skills and the ability to work in a collaborative team environment
- Comfortable in navigating multi-disciplinary teams with respect
- Focus on code quality in terms of coverage, code reviews
- Excellent technical writing skills to communicate design, requirements, flows, architecture
- Fluent in one of these programming languages: Golang, Scala, Java,
- Comfortable in one of these scripting languages: Javascript, python
- Solid understanding of algorithms, data structures, and software design principles.
- Experience with version control systems such as Git.
---- Preferred Qualifications ----
- Experience in machine learning, GenAI, or LLM technologies.
- Experience with building conversational assistants
- Dialog management systems like Google Dialogflow, Amazon Alexa
- Familiarity with large scale distributed systems like Kafka and cloud platforms like AWS, GCP, or Azure.
- Familiarity with communication channel interfaces eg: Whats App, SMS, slack
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 fuelds progress. What moves us, moves the world - let's move it forward, together.
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.
Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
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
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
News & Buzz
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Source: NYC.gov
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Source: CBT News
News
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