1 day ago
Base Salary
$184k - $357k/yr
Responsibilities
- Research and develop techniques to GPU-accelerate high-performance databases, ETL, and data analytics applications.
- Analyze and optimize complex data-intensive workloads for current GPU architectures.
- Investigate hardware and system bottlenecks, including CPU/GPU memory subsystems.
- Collaborate with research, hardware, system software, libraries, and tools teams to influence next-generation architectures, software, and programming models.
- Work with industry and academic partners to advance data processing using NVIDIA products.
Requirements
- Master’s or PhD in Computer Science, Computer Engineering, or a related computationally focused science field, or equivalent experience.
- 8+ years of experience.
- Programming fluency in C/C++ with deep understanding of algorithms and software design.
- Hands-on experience with low-level parallel programming such as CUDA, OpenACC, OpenMP, MPI, pthreads, or TBB.
- In-depth knowledge of CPU/GPU architecture fundamentals, especially memory subsystems.
- Domain expertise in high-performance databases, ETL, data analytics, or vector databases.
- Preferred experience optimizing database operators or query planners, parallel or distributed frameworks such as Spark, vector database indexes, CUDA kernels, compression, storage systems, networking, or distributed computer architectures.
Benefits
- Base salary ranges from $184,000-$287,500 for Level 4 and $224,000-$356,500 for Level 5, depending on location, experience, and comparable employee pay.
- Eligible for equity and benefits.
- Applications are accepted at least until September 12, 2026.
- NVIDIA uses AI tools in its recruiting processes.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.