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Google
Google

Organizing the world's information and making it universally accessible.

Senior Research Scientist, Search Ads Quality

职能机器学习
级别资深
方式现场办公
类型全职
发布3周前
立即申请
  • Solve Ads issues while maintaining high-quality and low-latency performance standards.

  • Collaborate with Ads and Research teams to design and implement solutions.

  • Utilize various AI technologies, including Agentic AI, Large Language Model (LLM) fine-tuning, and Large Embedding Model (LEM) optimization.

  • Work alongside AI/ML experts from various fields to address critical advertising problems.

  • Publish novel research and share technical insights with the global academic community.

  • PhD degree in Computer Science, a related field, or equivalent practical experience.

  • 2 years of experience leading a research agenda.

  • Experience in one or more areas of Machine Learning, such as AI algorithms, AI platforms or Generative AI Agents.

  • One or more scientific publication submissions for conferences, journals, or public repositories (such as NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, NAACL, CVPR, etc.).

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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

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