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Cuda Software Engineer Jobs (NOW HIRING)

Nvidia

OR · On-site

$122K - $161K/yr

NVIDIA is seeking a Senior Software Engineer, NCCL and CUDA specialization to join our Cloud Service Provider (CSP)Engagements team, focusing on ML software stack functionality and performance for ...

Nvidia

OR · On-site

$122K - $161K/yr

... CUDA programming and kernel optimization. * A strong analytical approach with experience using profiling tools to deeply understand software performance on hardware. * Experience profiling and ...

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How much do cuda software engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for cuda software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a CUDA Software Engineer, and why are they important?

To thrive as a CUDA Software Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid understanding of GPU architectures, typically supported by a computer science or related degree. Familiarity with NVIDIA CUDA Toolkit, GPU debugging/profiling tools, and experience with performance optimization are essential. Analytical thinking, problem-solving, and effective teamwork skills help you tackle complex computational challenges and collaborate on large-scale projects. These skills are crucial to efficiently develop high-performance GPU-accelerated applications and deliver optimized solutions in demanding technical environments.

What are some common challenges Cuda Software Engineers face when optimizing code for GPU performance?

Cuda Software Engineers often encounter challenges related to memory management, such as minimizing data transfers between CPU and GPU and optimizing memory access patterns to avoid bottlenecks. Additionally, ensuring code scalability across different GPU architectures and achieving efficient parallelization can be complex. Collaborating closely with data scientists, hardware engineers, and other developers is essential to troubleshoot performance issues and maximize throughput in real-world applications.

What are CUDA Software Engineers?

CUDA Software Engineers are specialists who develop software using NVIDIA's CUDA (Compute Unified Device Architecture) platform to leverage the parallel processing power of GPUs. They optimize algorithms and applications for high performance on CUDA-enabled devices, often in fields like scientific computing, machine learning, and graphics. Their work involves writing and debugging code in languages such as C, C++, or Python with CUDA extensions, and collaborating with teams to ensure efficient execution of compute-intensive tasks.
Senior Software Engineer, NCCL and CUDA - CSP Engagements

Senior Software Engineer, NCCL and CUDA - CSP Engagements

NVIDIA

Santa Clara, CA • On-site

$143K - $189K/yr

Full-time

Posted 29 days ago

Job description

Job Summary:
NVIDIA is seeking a Senior Software Engineer with NCCL and CUDA specialization to join their Cloud Service Provider Engagements team, focusing on enhancing ML software stack performance for datacenter products. The role involves collaborating with customers to address functional and performance issues in libraries, applying technical expertise to optimize workloads, and delivering integrated solutions aligned with NVIDIA's ecosystem.
Responsibilities:
• Engage with our CSPs to root cause functional and performance issues in NCCL and CUDA libraries.
• Analyze and improve multi-GPU workloads performance through profiling, benchmarking, and tuning.
• Understand and solve NCCL and NVSHMEM data movement issues in multi-node clusters.
• Understand and solve CUDA porting issues for customer workloads.
• Apply datacenter-specific scheduling and topologies for optimal performance
• Debug and resolve complex issues related to GPU computation, memory, and transports.
• Collaborate with customers to understand their workload integration specific challenges to NCCL and CUDIA libraries and suggest tailored solutions aligned with the NVIDIA ecosystem.
• Collaborate with AE, FAE, and solution architects to deliver integrated customer solutions and technical documentation.
• Collaborate with internal teams to help customers use the latest advancements in CUDA and in NCCL.
Qualifications:
Required:
• Experience with parallel programming models and with communication libraries (MPI, NCCL, NVSHMEM) run time.
• Experience with performance optimization and profiling tools (e.g., Nsight, nvprof)
• Excellent C/C++ programming and debugging skills, with experience in CUDA development.
• Good exposure to PCIe and NVLINK.
• Deep understanding of operating systems and data-center system architecture.
• Knowledge of high-performance networking like InfiniBand, and RoCE.
• Proficient understanding of compute, networking and cloud deployment, specifically on bare-metal and VMs.
• BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience).
• Familiarity with containers, cloud provisioning and scheduling tools such as Docker, Kubernetes, SLURM, and Ansible.
• 8+ years of system software validation experience.
• Ability to communicate effectively and collaborate with partner and customer teams.
Preferred:
• Strong software architecture experience.
• Experience with deep learning workloads training and inferencing
• Experience conducting performance benchmarking and developing tooling on HPC clusters
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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