Used Tools & Technologies
Not specified
Required Skills & Competences ?
System Administration @ 4 Linux @ 4 Python @ 4 Machine Learning @ 4 Bash @ 4 Communication @ 7 Mathematics @ 4 Networking @ 4 Debugging @ 4 GPU @ 4Details
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence.
Responsibilities
- Provide engineering solutions to operationalize the latest GPU Computing and Networking products and software stacks.
- Ensure technical relationships with internal and external engineering teams.
- Assist systems, machine learning/deep learning engineers in building creative solutions based on NVIDIA technology.
- Be an internal reference for system administration, at-scale fabric health and performance analysis.
- Develop datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community.
Requirements
- 5+ years of experience using accelerated computing for datacenter/HPC-based Enterprise computing solutions.
- Solid understanding of accelerated computing scheduling and I/O stacks.
- Programming/scripting experience in C/C++, Python, Bash.
- Experience supporting high performance computing or deep learning in engineering or academic research communities.
- Experience with parallel filesystems.
- Strong teamwork and communication skills, both verbal and written.
- Ability to multitask effectively in a dynamic environment.
- Experience deploying and maintaining high speed networks like Infiniband or Ethernet for compute and storage traffic.
- BS (or equivalent experience) in Engineering, Mathematics, Physics, or Computer Science; MS or PhD desirable.
Ways to stand out from the crowd
- Hands-on experience debugging large scale IB/Ethernet/NVLink fabrics.
- Experience with Spectrum-X fabric deployments.
- Deep Learning framework skills.
- Exposure to using and deploying telemetry and visualization pipelines.
- Exposure to container technology and Linux performance tools.
Benefits
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. Equity eligibility and additional benefits apply. NVIDIA values diversity and is an equal opportunity employer.