
Organizing the world's information and making it universally accessible.
Senior Software Engineer, AI/ML Infrastructure
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a software engineer in Cloud ML Compute Services, you will focus on driving advancement in AI infrastructure. The team manages key challenges by optimizing ML workload performance at every layer across the technical stack from networking and data storage to ML models. The team is dedicated to providing AI developers with high-performance experience on Google's AI infrastructure.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
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Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
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Optimize performance on Google's AI infrastructure across the technical stack.
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Conduct the performance profiling, debugging, and troubleshooting of AI/ML training and inference workloads.
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Develop tools and software for our AI/ML Infrastructure to deliver excellent developer experience.
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Partner closely with cross-functional, cross-regional teams to ensure our AI/ML infrastructure delivers exceptional value and drives success for our customers.
Minimum qualifications
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Bachelor's degree or equivalent practical experience.
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5 years of experience with software development in one or more programming languages.
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3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
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3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications
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Master's degree or PhD in Computer Science or related technical fields.
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5 years of experience with data structures and algorithms.
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Experience with distributed computing leveraging GPUs or TPUs.
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Ability to scope and solve ambiguous problems, and grow in a fluid environment where AI technologies are continuously advancing.
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关于Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
10条评价
4.5
10条评价
工作生活平衡
3.2
薪酬
4.3
企业文化
4.1
职业发展
4.2
管理层
3.8
82%
推荐率
优点
Great benefits and perks
Innovative and interesting work
Career development and learning opportunities
缺点
High pressure and expectations
Long hours and heavy workload
Fast-paced and overwhelming environment
薪资范围
57,503个数据点
Junior/L3
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
L3
L4
L5
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
面试评价
9条评价
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