NVIDIASenior System Software Engineer - AI Performance and Efficiency Tools
NVIDIA is hiring a Senior System Software Engineer - AI Performance and Efficiency Tools in Shanghai, China. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- Tools and skills the posting cites include PyTorch, TensorFlow and C.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
Develop internal profiling, debugging, and benchmarking tools for large-scale AI workloads running on NVIDIA GPU clusters.
A key part of NVIDIA's strength is our sophisticated analysis / debugging tools that empower NVIDIA engineers to improve perf and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and SW/HW teams running AI workload in GPU cluster.
As a member of the software development team, we will work with users from different departments like Architecture teams, Software teams. Our work brings the users intuitive, rich and accurate insight in the workload and the system, and empower them to find opportunities in software and hardware, build high level models to propose and deliver the best hardware and software to our customers, or debugging tricky failures and issues to help improve the performance and efficiency of the system.
What you’ll be doing:
Build internal profiling and analysis tools for AI workloads at large scale
Build debugging tools for common encountered problems like memory or networking
Create benchmarking and simulation technologies for AI system or GPU cluster
Partner with HW architects to propose new features or improve existing features with real world use cases
What we need to see:
BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development
Strong software skills in design, coding (C++ and Python), analytical, and debugging
Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference.
Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking
Experience with NVIDIA GPUs, CUDA Programming and NCCL
Motivated self-starter with strong problem-solving skills and customer-facing communication skills
Passion for continuous learning. Ability to work concurrently with multiple global groups
Ways to stand out from the crowd:
Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms
Solid experience in large AI job performance analysis for training/inference workload
Knowledge of Linux device drivers and/or compiler implementation
Knowledge of GPU and/or CPU architecture and general computer architecture principles
How we rate this
Senior System Software Engineer - AI Performance and Efficiency Tools at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a project where software engineering was part of your work. What did you do?
- Tell me about a project where performance analysis was part of your work. What did you do?
- Tell me about a project where debugging was part of your work. What did you do?
- Tell me about a project where distributed training was part of your work. What did you do?
- Walk me through how you've used PyTorch in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Software Engineering, Performance Analysis, Debugging, Distributed Training, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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