Quick summary
- Work type
- Remote
- Location
- Santa Clara, CA
- Salary
- $152,000–$241,500 / yr
- Posted
- 11 days ago
Market check
Salary context
Competitive pay
How this pay compares to similar roles
Similar $201k
This role $197k
$141k
most similar roles pay here
$252k
This role pays more than 52% of similar roles. Most pay $167,000–$235,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $201k for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has 563 open roles on FindRole.
Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.
Most-posted roles
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At a glance
TL;DR · Senior System Software Engineer - GPU Performance
As a Performance Engineer at NVIDIA, you will join our dynamic team focused on enhancing communication libraries for deep learning and high-performance computing applications. Your primary responsibilities include conducting performance analysis on multi-GPU and multi-node clusters, evaluating proof-of-concepts, and triaging customer-reported issues. You will also build tools to visualize and analyze large amounts of performance data while collaborating with a global team. Ideal candidates have an M.S. or PhD in Computer Science and at least three years of experience with parallel programming and communication runtimes like MPI, NCCL, UCX, or NVSHMEM. Proficiency in C/C++, Python scripting, and familiarity with systems software fundamentals are essential. Additional skills such as Infiniband/Ethernet network expertise, CUDA programming, and knowledge of deep learning frameworks will be highly beneficial.
Skills
What you'll do
- Conduct performance characterization and analysis on multi-GPU and multi-node clusters.
- Study interaction of communication libraries with hardware and software components.
- Evaluate proof-of-concepts and conduct trade-off analyses for solutions.
- Triage and root-cause performance issues reported by customers.
- Build tools and infrastructure to visualize and analyze performance data.
What we're looking for
- M.S. or PhD in Computer Science with 3+ years of HPC and performance engineering experience.
- Expertise in parallel programming and at least one communication runtime (MPI, NCCL, UCX).
- Proficient in conducting performance benchmarking on large-scale HPC clusters.
- Strong understanding of computer system architecture and HW-SW interactions.
- Skilled in implementing micro-benchmarks in C/C++ and debugging across the stack.
- Familiarity with Infiniband/Ethernet networks, RDMA, and congestion control.
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