refresh

トレンド企業

トレンド企業

採用

求人NVIDIA

Senior Deep Learning Communication Architect

NVIDIA

Senior Deep Learning Communication Architect

NVIDIA

2 Locations

·

On-site

·

Full-time

·

2mo ago

報酬

$184,000 - $356,500

福利厚生

Healthcare

Learning

Equity

Flexible Hours

必須スキル

React

JavaScript

PostgreSQL

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What You'll Be Doing:

  • The software architecture group at NVIDIA has openings for a Deep Learning Communication Architect. We scale the DNN models and training/inference frameworks to systems with hundreds of thousands of nodes.

  • Optimizing communication performance: Identify and eliminate bottlenecks in data transfer and synchronization during distributed deep learning training and inference.

  • Designing efficient communication protocols: Develop and implement communication algorithms and protocols tailored for deep learning workloads, minimizing communication overhead and latency.

  • Hardware and software co-craft: Collaborate with hardware and software teams to craft systems that effectively apply high-speed interconnects (e.g., NVLink, Infini Band, SPC-X) and communication libraries (e.g., MPI, NCCL, UCX, UCC, NVSHMEM).

  • Exploring innovative communication technologies: Research and evaluate new communication technologies and techniques to enhance the performance and scalability of deep learning systems.

  • Developing and implementing solutions: Build proofs-of-concept, conduct experiments, and perform quantitative modeling to validate and deploy new communication strategies.

What We Need to See:

  • A Ph.D., Masters, or BS in Computer Science (CS), Electrical Engineering (EE), Computer Science and Electrical Engineering (CSEE), or a closely related field or equivalent experience.

  • 6 years of experience in Building DNNs, Scaling of DNNs, Parallelism of DNN frameworks, or deep learning training and inference workloads.

  • Experience in evaluating, analyzing, and optimizing LLM training and inference performance of state-of-the-art models on cutting-edge hardware.

  • Deep understanding of parallelism techniques, including Data Parallelism, Pipeline Parallelism, Tensor Parallelism, Expert Parallelism, and FSDP.

  • Understanding of the emerging serving architectures like Disaggregated Serving and inference servers like Dynamo and Triton

  • Proficiency in developing code for one or more deep neural network (DNN) training and Inference frameworks, such as Py Torch, TensorRT-LLM, vLLM, SGLang.

  • Strong programming skills in C and Python.

  • Familiarity with GPU computing, including CUDA and OpenCL, and familiarity with Infini Band and RoCE networks. CUDA and OpenCL, and familiarity with Infini Band and RoCE networks.

Ways to Stand Out from the Crowd:

  • Prior contributions to one or more DNN training and Inference frameworks as part of your previous work experience.

  • Deep understanding and contributions to the scaling of LLMs on large-scale systems.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and talented people in the world working for us. If you're creative and passionate about developing cloud services we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 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.

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

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