Overview
Remote
On Site
USD 148,000.00 per year
Full Time
Skills
High Performance Computing
Visualization
Science
ROOT
GPU
Microsoft Azure
Amazon Web Services
Google Cloud
Google Cloud Platform
Storage
Customer Engagement
Parallel Computing
Communication
MPI
C
C++
Code Optimization
Performance Analysis
Quality Assurance
Research
Artificial Intelligence
Computer Networking
InfiniBand
Ethernet
Remote Direct Memory Access
Linux
Scripting Language
Python
Cloud Computing
Provisioning
Scheduling
Docker
Kubernetes
Ansible
Adaptability
Benchmarking
HPC
System Administration
ESP
Debugging
Network Administration
CUDA
Machine Learning (ML)
Deep Learning
PyTorch
TensorFlow
Recruiting
Promotions
SAP BASIS
Law
Job Details
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 the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication runtimes like NCCL and NVSHMEM for Deep Learning and HPC applications. We are looking for a motivated Partner Enablement Engineer to guide our key partners and customers with NCCL. Most DL/HPC applications run on large clusters with high-speed networking (Infiniband, RoCE, Ethernet). This is an outstanding opportunity to get an end to end understanding of the AI networking stack. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
What we need to see:
Ways to stand out from the crowd:
The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
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.
We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver communication runtimes like NCCL and NVSHMEM for Deep Learning and HPC applications. We are looking for a motivated Partner Enablement Engineer to guide our key partners and customers with NCCL. Most DL/HPC applications run on large clusters with high-speed networking (Infiniband, RoCE, Ethernet). This is an outstanding opportunity to get an end to end understanding of the AI networking stack. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
- Engage with our partners and customers to root cause functional and performance issues reported with NCCL
- Conduct performance characterization and analysis of NCCL and DL applications on groundbreaking GPU clusters
- Develop tools and automation to isolate issues on new systems and platforms, including cloud platforms (Azure, AWS, Google Cloud Platform, etc.)
- Guide our customers and support teams on HPC knowledge and standard methodologies for running applications on multi-node clusters
- Document and conduct trainings/webinars for NCCL
- Engage with internal teams in different time zones on networking, GPUs, storage, infrastructure and support.
What we need to see:
- B.S./M.S. degree in CS/CE or equivalent experience with 5+ years of relevant experience. Experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)
- Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
- Experience working with engineering or academic research community supporting HPC or AI
- Practical experience with high performance networking: Infiniband/RoCE/Ethernet networks, RDMA, topologies, congestion control
- Expert in Linux fundamentals and a scripting language, preferably Python
- Familiar with containers, cloud provisioning and scheduling tools (Docker, Docker Swarm, Kubernetes, SLURM, Ansible)
- 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 conducting performance benchmarking and developing infrastructure on HPC clusters. Prior system administration experience, esp for large clusters. Experience debugging network configuration issues in large scale deployments
- Familiarity with CUDA programming and/or GPUs. Good understanding of Machine Learning concepts and experience with Deep Learning Frameworks such PyTorch, TensorFlow
- Deep understanding of technology and passionate about what you do
The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.