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トレンド企業

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求人NVIDIA

Senior Deep Learning Performance Architect

NVIDIA

Senior Deep Learning Performance Architect

NVIDIA

2 Locations

·

On-site

·

Full-time

·

2mo ago

報酬

$152,000 - $287,500

福利厚生

Equity

必須スキル

C

C++

Python

CUDA

Machine Learning

Deep Learning

Computer Architecture

We are now looking for a Senior Deep Learning Performance Architect!

NVIDIA seeks a Senior DL Performance Architect to join our group of pioneers who enjoy pushing AI Inference performance boundaries. Our team focuses on ambitious hardware-software co-design to speed AI Inference workloads. This role gives an outstanding opportunity to develop world-class performance strategies, guide future GPU architecture decisions, and lead AI innovation. If you are passionate about AI efficiency Pareto curves, have a proven record of modeling LLM performance and architecting AI systems, and enjoy optimizing every cycle, this role may be perfect for you!

What you'll be doing:

  • Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency

  • Construct, investigate, and test popular deep learning algorithms and applications

  • Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications

  • Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture

  • Collaborate across the company to guide the direction of AI, working with software, research, and product teams

What we need to see:

  • A MS or PhD in a relevant field (CS, EE, Math) or equivalent experience, with 5 years of relevant experience

  • Strong mathematical foundation in machine learning and deep learning

  • Expert programming skills in C, C, and/or Python

  • Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack

  • Strong knowledge and coursework in computer architecture

Ways to stand out from the crowd:

  • Background with systems-level performance modeling, profiling, and analysis

  • Experience in characterizing and modeling system-level performance, accomplishing comparison studies, and documenting and publishing results

  • Background in improving AI Inference workloads by developing CUDA kernels or compilers for custom ASIC hardware

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 14, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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応募クリック数

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模擬応募者数

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スクラップ

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NVIDIAについて

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

従業員数

Santa Clara

本社所在地

$4.57T

企業価値

レビュー

4.1

10件のレビュー

ワークライフバランス

3.5

報酬

4.2

企業文化

4.3

キャリア

4.5

経営陣

4.0

75%

友人に勧める

良い点

Great culture and supportive environment

Smart colleagues and excellent people

Cutting-edge technology and learning opportunities

改善点

Team-dependent experience and outcomes

Work-life balance issues with long hours

Politics and influence over competence

給与レンジ

73件のデータ

L3

L4

L5

L3 · Data Scientist IC2

0件のレポート

$177,542

年収総額

基本給

-

ストック

-

ボーナス

-

$150,910

$204,174

面接体験

7件の面接

難易度

3.1

/ 5

体験

ポジティブ 0%

普通 86%

ネガティブ 14%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

System Design Interview

6

Team Review

よくある質問

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR