채용

Software Engineering Manager - GPU Communications Libraries
US, CA, Santa Clara
·
On-site
·
Full-time
·
1mo ago
필수 스킬
Go
Linux
We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. DL and HPC applications have a huge compute demand already and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes.
Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! We are looking for a technical leader to manage our NVSHMEM and UCX libraries. This is an outstanding opportunity to push the limits on the state-of-the-art and deliver platforms the world has never seen before. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
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Lead, mentor, and grow your library engineering team and be responsible for the planning and execution of projects as well as the quality, and performance of your libraries.
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This is a technical leadership role so you will participate in feature design and implementation.
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Interact with internal and external partners and researchers to understand their use cases and requirements. Collaborate with engineering teams, program and product management, and partners to define the product roadmap.
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Continuously review and identify improvement opportunities in established processes, infrastructure, and practices to ensure the teams are executing in the most efficient and transparent manner.
What we need to see:
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10+ overall years of experience in the software industry with specialization in HPC networking or system software.
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4+ years of management experience.
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BS, MS, or Ph.D. in CS, CE, EE (related technical field) or equivalent experience.
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Prior systems software or communication runtime or high performance networking software development experience with a successful track record of taking several complex software features or products through the full product life cycle.
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Strong understanding of computer system architecture, operating systems principles (aka systems software fundamentals), HW-SW interactions and performance analysis/optimizations.
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Excellent C/C++ programming and debugging skills in Linux.
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Experience balancing multiple projects with competing priorities.
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Flexibility to work and communicate effectively across different teams and timezones.
Ways to stand out from the crowd:
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Experience with parallel programming models (MPI, SHMEM) and at least one communication runtime (MPI, NCCL, NVSHMEM, OpenSHMEM, UCX, UCC). Experience with programming using CUDA, MPI, OpenMP, OpenACC, pthreads.
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Background with RDMA, high-performance networking technologies (Infini Band, RoCE, Ethernet, EFA), network architecture and network topologies. Knowledge of HPC and ML/DL fundamentals.
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Experience with Deep Learning Frameworks such Py Torch, Tensor Flow, etc.
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. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, 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 2, and 224,000 USD - 356,500 USD for Level 3.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 18, 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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NVIDIA 소개

NVIDIA
PublicA 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
Junior/L3
Mid/L4
Junior/L3 · Analyst
7개 리포트
$170,275
총 연봉
기본급
$130,981
주식
-
보너스
-
$155,480
$234,166
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
뉴스 & 버즈
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
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NaNw ago
NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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NaNw ago
NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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