招聘
福利待遇
•Healthcare
•Remote Work
•Equity
•Unlimited Pto
•Learning
必备技能
Python
Apache Spark
Airflow
About the job
Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed, fault-tolerant systems. SRE ensures that Google Cloud's services—both our internally critical and our externally-visible systems—have reliability, uptime appropriate to customer's needs and a fast rate of improvement. Additionally SRE’s will keep an ever-watchful eye on our systems capacity and performance.
Much of our software development focuses on optimizing existing systems, building infrastructure and eliminating work through automation. On the SRE team, you’ll have the opportunity to manage the complex challenges of scale which are unique to Google Cloud, while using your expertise in coding, algorithms, complexity analysis and large-scale system design. SRE's culture of intellectual curiosity, problem solving and openness is key to its success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to create an environment that provides the support and mentorship needed to learn and grow.
In this role, you will play a pivotal role in accelerating AI adoption and enhancing observability within SRE operations. You will be at the forefront of designing, building and maintaining the core infrastructure and tools that empower SRE teams to leverage the power of AI and gain insights into system behavior.
Responsibilities
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Develop base APIs for essential AI functionalities (similarity, clustering, RAG) across various data sources. Collaborate with SRE teams to design, implement, and evaluate AI features, ensuring their quality and effectiveness.
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Develop AI features like incident-support case matcher, similarity search, bug analyzer, to improve engineering efficiency and customer satisfaction.
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Implement production cohorting and regression attribution capabilities to enable insights into production workloads and aimed issue detection. Build and expand horizontal cloud monitoring Google Cloud Platform (GCP) products.
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Develop AI features for real-time suggestions, root cause analysis, and escalation decisions. Build AI-powered insights to identify operational trends and toil areas.
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Provide feedback and evaluation systems used to continuously improve the quality of AI features in SRE. Expand horizontal cloud monitoring coverage and leverage AI for proactive incident detection.
Minimum qualifications
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Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
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2 years of experience with software development in one or more programming languages.
Preferred qualifications
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Master's degree in Computer Science, Engineering, or a related field.
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2 years of experience designing, analyzing, and troubleshooting large-scale distributed systems.
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10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
3.7
25条评价
工作生活平衡
3.8
薪酬
4.2
企业文化
3.4
职业发展
3.9
管理层
2.8
68%
推荐给朋友
优点
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
缺点
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
薪资范围
57,502个数据点
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0份报告
$176,704
年薪总额
基本工资
-
股票
-
奖金
-
$150,298
$203,110
面试经验
9次面试
难度
3.4
/ 5
时长
14-28周
录用率
44%
体验
正面 0%
中性 56%
负面 44%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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