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Senior Deep Learning Framework Communications Engineer

NVIDIA

Senior Deep Learning Framework Communications Engineer

NVIDIA

US, CA, Santa Clara

·

On-site

·

Full-time

·

2mo ago

보상

$152,000 - $287,500

복지 및 혜택

Parental Leave

Equity

Learning

Healthcare

필수 스킬

Python

JavaScript

TypeScript

About the Role

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including Py Torch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?

Responsibilities

  • Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
  • Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities
  • Collaborate hands-on with teams working on the latest AI models
  • Improve AI compilers to hide communications or perform automatic fusion
  • Conduct in-depth AI workload performance characterization on multi-GPU clusters
  • Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads
  • Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms
  • Influence the roadmap of communication libraries
  • NCCL & NVSHMEM
  • Collaborate with a very dynamic team across multiple time zones

Qualifications

  • B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience
  • Development or integration experience with Deep Learning Frameworks such Py Torch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
  • Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cu Te)
  • Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
  • Experience conducting performance benchmarking on AI clusters
  • Familiarity with at least one performance profiler toolchain (Py Torch profiler, NVIDIA Nsight Systems)
  • Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
  • Adaptability and passion to learn new areas and tools
  • Flexibility to work and communicate effectively across different teams and timezones

Ways to Stand Out from the Crowd

  • Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI)
  • Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
  • Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cu Te, etc)
  • Experience with programming for compute & communication overlap in distributed runtimes
  • Experience with AI compiler pattern matching and lowering
  • Solid understanding of memory hierarchy, consistency model, and tensor layout

Compensation and Benefits

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.

Application Information

Applications for this job will be accepted at least until February 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

Equal Opportunity

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. NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

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NVIDIA 소개

NVIDIA

NVIDIA

Public

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

10,001+

직원 수

Santa Clara

본사 위치

$4.57T

기업 가치

리뷰

4.1

10개 리뷰

워라밸

3.5

보상

4.2

문화

4.3

커리어

4.5

경영진

4.0

75%

친구에게 추천

장점

Great culture and supportive environment

Smart colleagues and excellent people

Cutting-edge technology and learning opportunities

단점

Team-dependent experience and outcomes

Work-life balance issues with long hours

Politics and influence over competence

연봉 정보

73개 데이터

L3

L4

L5

L3 · Data Scientist IC2

0개 리포트

$177,542

총 연봉

기본급

-

주식

-

보너스

-

$150,910

$204,174

면접 경험

7개 면접

난이도

3.1

/ 5

경험

긍정 0%

보통 86%

부정 14%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Interview

5

System Design Interview

6

Team Review

자주 나오는 질문

Coding/Algorithm

System Design

Technical Knowledge

Behavioral/STAR