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Research Engineer, Paradigms of Intelligence

Google

Research Engineer, Paradigms of Intelligence

Google

·

On-site

·

Full-time

·

2w ago

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.

Paradigms of Intelligence (Pi), a research team at Google, brings together an interdisciplinary group of researchers, engineers, and philosophers to explore the fundamental building blocks of intelligence and the conditions under which it can emerge. Just as intelligence arose through billions of years of evolution, we believe that embracing a bottom-up approach – while drawing on insights from the physical, biological, and social sciences – will allow us to develop more efficient, adaptable, and human AI.

Responsibilities

  • Write product or system development code.

  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.

  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.

  • One or more scientific publication submissions for conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ALIFE, GECCO etc.).

Preferred qualifications

  • Experience in differentiable simulations and the intersection of deep learning with physical or biological systems (e.g., Artificial Life/ALife, morphogenesis, or dynamic texture synthesis).

  • Experience developing real-time interactive systems or large-scale dataset modeling (e.g., inverse modeling of complex textures).

  • Experience in mathematical foundation including Statistical Field Theory, Linear Algebra, and Stochastic Processes, evidenced by academic honors (e.g., National Olympiad medals or thesis awards).

  • Proficiency in deep learning frameworks (Py Torch, JAX).

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Googleについて

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

従業員数

Mountain View

本社所在地

$1,700B

企業価値

レビュー

3.7

25件のレビュー

ワークライフバランス

3.8

報酬

4.2

企業文化

3.4

キャリア

3.9

経営陣

2.8

68%

友人に勧める

良い点

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

改善点

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

給与レンジ

57,502件のデータ

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0件のレポート

$176,704

年収総額

基本給

-

ストック

-

ボーナス

-

$150,298

$203,110

面接体験

9件の面接

難易度

3.4

/ 5

期間

14-28週間

内定率

44%

体験

ポジティブ 0%

普通 56%

ネガティブ 44%

面接プロセス

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense