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职位Google

Technical Program Manager II, AI/ML, Google Ads

Google

Technical Program Manager II, AI/ML, Google Ads

Google

·

On-site

·

Full-time

·

1w ago

  • Define, scope, and manage LLM guide projects, ensuring timely delivery and strict adherence to scope. Build highly detailed project plans, track progress, and orchestrate seamless execution.

  • Engage deeply in technical design and implementation discussions. Understand the intricacies of Gemini models, serving architectures, and quality evaluation requirements.

  • Guide the development of highly efficient evaluation frameworks. Drive initiatives to optimize human evaluation pipelines and advance LLM as a rater methodologies, ensuring our models meet exceptionally high quality bars at scale.

  • Partner with leadership and product managers to define the long-term goal and Objectives and Key Results (OKRs) for our initiatives.

  • Bridge the gap between engineering complexities and business needs. Translate complex business goals into actionable, multi-quarter technical roadmaps.

  • Bachelor's degree in a technical field, or equivalent practical experience.

  • 2 years of experience in program management.

  • Experience managing ML or LLM model development programs.

  • Experience working with AI algorithms.

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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