Senior Software Engineer - Parallel Computing Systems

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

Join a leading company at the forefront of AI compilation as a Senior Software Engineer specializing in Parallel Computing Systems. You'll work on developing cutting-edge compiler technology, collaborating with top experts to optimize deep learning models and push the boundaries of GPU performance. This is an opportunity to influence future hardware design while working alongside a diverse team dedicated to fostering innovation and inclusivity.

Benefits

Equity options

Comprehensive benefits package

Qualifications

• 4+ years advanced C++ programming experience.
• Expertise in parallel programming and performance-critical code.
• Experience with systematic performance optimization.

Responsibilities

• Design algorithms for optimized code from deep learning programs.
• Build GPU-aware CPU runtime systems to maximize performance.
• Collaborate with NVIDIA engineers to enhance GPU architecture.

Skills

CUDA optimization

C++ programming

Parallel programming

Performance optimization

Multi-threading

Education

MS or PhD in Computer Science or related field

Tools

OpenMP

MPI

NCCL

Job description

Senior Software Engineer - Parallel Computing Systems page is loaded

Senior Software Engineer - Parallel Computing Systems

Apply locations US, CA, Santa Clara US, CA, Remote time type Full time posted on Posted 3 Days Ago job requisition id JR1998609

Do you have expertise in CUDA kernel optimization, C++ systems programming, or compiler infrastructure? Join NVIDIA'snvFuser team to build the next-generation fusion compiler that automatically optimizes deep learning models for workloads scaling to thousands of GPUs! We're looking for engineers who excel at parallel programming and systems-level performance work and want to directly impact the future of AI compilation.

The Deep Learning Frameworks Team @ NVIDIA is responsible for buildingnvFuser , an advanced compiler that sits at the intersection of compiler technology and high-performance computing. You'll work closely with the PyTorch Core team and collaborate withLightning-AI/Thunder , which integratesnvFuser to accelerate PyTorch workloads. We collaborate with hardware architects, framework maintainers, and optimization experts to create compiler infrastructure that advances GPU performance, developing manual optimization techniques into systematic, automated compiler optimizations.

What you'll be doing

As annvFuser engineer, you'll work on exciting challenges in compiler technology and performance optimization! You'll design algorithms that generate highly optimized code from deep learning programs and build GPU-aware CPU runtime systems that coordinate kernel execution for maximum performance. Working directly with NVIDIA's hardware engineers, you'll master the latest GPU architectures while collaborating with optimization specialists to develop innovative techniques for emerging AI workloads. From debugging performance bottlenecks in thousand-GPU distributed systems to influencing next-generation hardware design, we push the boundaries of what's possible in AI compilation.

What we need to see

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).

• 4+ years advanced C++ programming with large codebase development, template meta-programming, and performance-critical code.

• Strong parallel programming experience with multi-threading, OpenMP, CUDA, MPI, NCCL, NVSHMEM, or other parallel computing technologies.

• Shown experience with low-level performance optimization and systematic bottleneck identification beyond basic profiling.

• Performance analysis skills: experience analyzing high-level programs to identify performance bottlenecks and develop optimization strategies.

• Collaborative problem-solving approach with adaptability in ambiguous situations, first-principles based thinking, and a sense of ownership.

• Excellent verbal and written communication skills.

Ways to stand out from the crowd

• 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, performance profiling, and demonstrated track record of rapid learning.

• Expertise with distributed parallelism techniques, tensor operations, auto-tuning, or performance modeling.

The base salary range is 184,000 USD - 356,500 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.