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职位Google

Machine Learning Software Engineer, Decision Forests

Google

Machine Learning Software Engineer, Decision Forests

Google

placeZürich, Switzerland

·

On-site

·

Full-time

·

2mo ago

福利待遇

Remote Work

Healthcare

Equity

必备技能

Python

TensorFlow

PyTorch

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

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.

Responsibilities

  • Take co-ownership of new feature development (e.g., design, implementation, UX experiments, maintenance), drive corresponding applied research (reading papers, experimentation and benchmarking, possibly attending/publishing-in conferences), client collaboration (ranging from small consultations to deep engagements), and collaboration with other researchers.

  • Develop training capability on GPU and TPU of oblique, and other complex, forest models.

  • Design and productionize continuous learning algorithms and other tools/capabilities to make models to data distribution drift, training data storage policies, prediction churn, and removal/update of input signal.

  • Improve anomaly detection algorithms and productionize them into highly usable and integrated features.

  • Interact and collaborate (e.g., brainstorming, cross-project collaboration) with other topics, notably graph neural networks and agents.

Minimum qualifications

  • Bachelor's degree or equivalent practical experience.

  • 5 years of experience with software development in one or more programming languages.

  • 2 years of experience with C++ and Python.

  • Experience with machine learning/AI in a software development environment.

Preferred qualifications

  • 5 years of experience with data structures and algorithms.

  • Experience with one or more neural network frameworks: Py Torch, Tensor Flow or Jax.

  • Experience with applied machine learning/machine learning research.

  • Experience with decision trees.

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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