Senior Software Engineer - Parallel Computing Systems

at Nvidia
📍 Santa Clara, United States
USD 184,000-356,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Algorithms @ 4 Distributed Systems @ 4 Communication @ 4 Parallel Programming @ 4 Performance Optimization @ 4 PyTorch @ 4 CUDA @ 7 GPU @ 4

Details

Join NVIDIA's nvFuser team to build the next-generation fusion compiler that automatically optimizes deep learning models for workloads scaling to thousands of GPUs. This role focuses on compiler technology, systems-level performance, and parallel programming to improve GPU performance for AI workloads.

Responsibilities

  • Design algorithms that generate highly optimized code from deep learning programs.
  • Build GPU-aware CPU runtime systems that coordinate kernel execution for maximum performance.
  • Debug and identify performance bottlenecks in large-scale (thousand-GPU) distributed systems.
  • Collaborate with hardware architects, framework maintainers (including the PyTorch Core team), and optimization experts to develop systematic compiler optimizations from manual techniques.
  • Influence next-generation hardware design through performance-driven compiler work.

Requirements

  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
  • 4+ years of advanced C++ programming with large codebase development, template metaprogramming, and performance-critical code.
  • Strong parallel programming experience with technologies such as multi-threading, OpenMP, CUDA, MPI, NCCL, NVSHMEM, or other parallel computing frameworks.
  • Demonstrated experience with low-level performance optimization and systematic bottleneck identification beyond basic profiling.
  • Performance analysis skills: experience analyzing high-level programs to find performance bottlenecks and develop optimization strategies.
  • Collaborative problem-solving approach, adaptability in ambiguous situations, first-principles thinking, and strong ownership.
  • Excellent verbal and written communication skills.

Ways to stand out

  • Experience with HPC / scientific computing: CUDA optimization, GPU programming, numerical libraries (cuBLAS, NCCL), or distributed computing.
  • Compiler engineering background: LLVM, GCC, domain-specific language design, program analysis, or IR transformations and optimization passes.
  • Deep technical foundation in CPU/GPU architectures, numeric libraries, modular software design, or runtime systems.
  • Experience with large software projects, advanced performance profiling, and a demonstrated track record of rapid learning.
  • Expertise with distributed parallelism techniques, tensor operations, auto-tuning, or performance modeling.

Compensation & Benefits

  • Base salary range (dependent on location, experience, and level):
    • Level 4: 184,000 USD - 287,500 USD
    • Level 5: 224,000 USD - 356,500 USD
  • Eligible for equity and benefits (see NVIDIA benefits).

Other details

  • Location: Santa Clara, CA, United States (see location field).
  • Employment type: Full time.
  • Applications accepted at least until July 29, 2025.
  • NVIDIA is an equal opportunity employer and values diversity in its workforce.