채용
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Become a trusted advisor to the top customers, helping them understand and incorporate AI accelerators into their overall cloud and IT strategy by designing training and inferencing platforms, using the accelerators Google Cloud has to offer.
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Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and bench marking.
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Design and implement complex, multi-host AI training and inferencing solutions on Google Cloud TPUs, focusing on scalability and performance tuning.
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Conduct performance profiling and optimization of customer models and data pipelines for the TPU architecture, identifying and resolving bottlenecks.
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Advise customers on best practices for integrating their MLOps workflows with the Google Cloud AI Platform ecosystem for TPU utilization.
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
In this role, you will understand the needs of our customers and help shape the future using AI technology. You will work with Google Cloud Platform's technology and complete AI stack and position the same to our customers in all verticals. You will support Google Cloud sales teams to pilot, and deploy Google Cloud’s industry leading AI/ML accelerators (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate with solutions using Google Cloud’s flexible and open AI infrastructure.
You will be working with Google customers on AI Infrastructure server and networking infrastructure deployments. You will guide customer discussions on network topologies, compute/storage and support bring up of server/network/cluster/cooling deployments. You will need to visit the customer data center during the bring up phase. You will serve as a technical expert on the Google Cloud AI infrastructure, specifically guiding customers through the architecture, deployment, and optimization of large-scale, cost-efficient training and inference jobs on Cloud TPUs.
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.
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Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
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10 years of experience with cloud native architectures and modern cloud infrastructure with networking - switching/routing for ethernet/RoCE/infiniband, in customer-facing or support roles.
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Experience developing and deploying models using deep learning frameworks (Tensor Flow, Py Torch, or JAX).
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총 지원 클릭 수
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모의 지원자 수
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스크랩
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Google 소개

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
직원 수
Mountain View
본사 위치
$1,700B
기업 가치
리뷰
3.7
25개 리뷰
워라밸
3.8
보상
4.2
문화
3.4
커리어
3.9
경영진
2.8
68%
친구에게 추천
장점
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
단점
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
연봉 정보
57,502개 데이터
Junior/L3
Mid/L4
Junior/L3 · Account Manager
955개 리포트
$235,140
총 연봉
기본급
$138,750
주식
$55,227
보너스
$41,164
$148,728
$383,799
면접 경험
9개 면접
난이도
3.4
/ 5
소요 기간
14-28주
합격률
44%
경험
긍정 0%
보통 56%
부정 44%
면접 과정
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
뉴스 & 버즈
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