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职位Google

Senior Manager, GPU Machine Learning Production

Google

Senior Manager, GPU Machine Learning Production

Google

·

On-site

·

Full-time

·

1w ago

  • Guide the transition of GPU production support from fragmented, NPI-specific task forces into a centralized, standing organization.

  • Develop and execute a comprehensive, multi-year roadmap for GPU fleet stability, capacity turn-up, and automated health management, aligning with broader Cloud and AI infrastructure goals.

  • Anticipate the support needs for next-generation GPU architectures and proactively build the capabilities required for seamless NPI to General Availability (GA) transitions.

  • Sponsor and drive the development of advanced telemetry, debugging tooling, and automated remediation systems to scale fleet management and significantly reduce operational toil.

  • Serve as the executive escalation point for critical, systemic hardware and software issues on GPU Superpods.

  • Bachelor’s degree, or equivalent practical experience.

  • 8 years of experience programming in C++, Java, Python, Kotlin or Go.

  • 5 years of experience in a technical leadership role.

  • 5 years of experience in a people management or team leadership role.

  • 5 years of experience with embedded systems.

  • 5 years of experience with software architecture.

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关于Google

Google

Google

Public

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

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