招聘
About the Role
We are seeking a strong Senior Engineer to contribute to the design, development, and scaling of our Compute Platform with a focus on Kubernetes orchestration and cloud-native infrastructure. You will help build and evolve the systems that power Uber's mission-critical applications, enabling developers across the company to deploy and operate services with speed, reliability, and security.
In this role, you will work on key architectural components, drive high-impact technical initiatives, and collaborate closely with cross-functional teams across product and infrastructure.
What you will do
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Design, build, and enhance core components of Uber's Kubernetes-based Compute Platform, focusing on reliability, scalability, and global availability.
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Implement and optimize Kubernetes controllers, operators, CRDs, and multi-cluster management features to support diverse workloads across on-prem and cloud environments.
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Work on runtime systems-containerd, Docker, CRI-O-improving image lifecycle, sandboxing, security, and end-to-end pod execution performance.
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Develop and evolve the infrastructure abstraction layers and APIs that enable developers to deploy, manage, and scale stateful, batch, and mission-critical services with minimal operational overhead.
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Lead technical initiatives around scheduling, autoscaling, resource management, and workload placement to improve cluster efficiency and ensure high availability.
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Collaborate with cross-functional teams including Networking, Storage, ML Infra, Developer Productivity, and Data Platform to build solutions and elevate the overall developer experience.
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Debug, troubleshoot, and resolve complex issues across Linux systems, container runtimes, Kubernetes control plane, and distributed compute workflows.
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Contribute to architectural discussions, influence long-term design decisions, and help maintain a high technical bar within the Compute Platform team.
What you'll need
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8+ years of software engineering experience, including expertise in distributed systems or infrastructure engineering.
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Bachelors degree in Compute Science or related field
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Experience in Golang, Java, Python, C/C++
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Background in large-scale backend infrastructure
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Knowledge of cluster management solutions such as Mesos or Kubernetes
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Understanding of container technologies such as docker or containerd
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Knowledge of operating systems and linux kernel
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
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