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职位Google

Senior Staff Software Engineer, AI/ML GenAI, Google Ads

Google

Senior Staff Software Engineer, AI/ML GenAI, Google Ads

Google

·

On-site

·

Full-time

·

1w ago

  • Design, develop, test, deploy, maintain, and enhance large scale software solutions.

  • Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.

  • Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.

  • Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of state-of-the-art GenAI solutions.

  • Bachelor’s degree or equivalent practical experience.

  • 8 years of experience programming in Python or C++.

  • 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

  • 5 years of experience with design and architecture; and testing/launching software products.

  • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

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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