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 libraries like NCCL and NVSHMEM for Deep Learning and HPC applications. We are looking for a motivated DevOps and Automation Engineer to help us increase our execution efficiency. Most DL and HPC applications run on large clusters with high-speed networking (Infiniband, RoCE). This is an outstanding opportunity going beyond the traditional DevOps roles and responsibilities. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What You Will Be Doing
As a Senior Software Engineer in the GPU Communications Group, you will utilize your knowledge and expertise in high availability network software to create, enhance, and maintain our GPU communication solutions. You will:
- Maintain and improve CI/CD systems (Gitlab, Github, Perforce)
- Develop tools and automation to deploy testing on new systems and platforms, including cloud platforms (Azure, AWS, GCP, etc.)
- Maintain internal cluster servers and Infiniband/RoCE networks
- Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information
- Collaborate with a very dynamic team across multiple time zones
What We Need To See
- B.S. or M.S. in Computer Science, or related field and 5+ years of relevant experience
- Excellent C/C++ programming and debugging skills
- Expert in a scripting language, preferably Python
- Proficient with Linux fundamentals
- 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, especially for large clusters
- Good understanding of Infiniband/RoCE networks and experience debugging network configuration issues
- Familiarity with CUDA programming and/or GPUs. Experience with Deep Learning Frameworks such as PyTorch, TensorFlow. Deep understanding of technology and passionate about what you do
The base salary range is 144,000 USD - 270,250 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.
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