Senior Solutions Architect, Data Processing

Senior Solutions Architect, Data Processing

Join NVIDIA as a Senior Solutions Architect, Data Processing. NVIDIA is currently seeking a Solutions Architect for High-Performance Databases. If you enjoy researching new algorithms and memory management techniques to accelerate databases on modern computer architectures, and investigating hardware and system bottlenecks to optimize performance of data‑intensive applications, this role may be for you.

NVIDIA has reinvented itself over two decades, with the invention of the GPU sparking the growth of the PC gaming market, revolutionizing parallel computing, and igniting modern AI. We are a “learning machine” that continuously evolves by adapting to new opportunities that are hard to solve and that matter to the world. Our mission is to amplify human imagination and intelligence.

• Research and develop techniques to GPU‑accelerate high‑performance database, ETL, and data analytics applications.
• Work directly with other technical experts in industry and academia to perform in‑depth analysis and optimization of complex data‑intensive workloads for the best performance on current GPU architectures.
• Influence the design of next‑generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA.
• Influence partners (industry and academia) to push the bounds of data processing with NVIDIA’s full product line.

• Masters or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent experience.
• 8+ years of experience.
• Programming fluency in C/C++ with a deep understanding of algorithms and software design.
• Hands‑on experience with low‑level parallel programming, e.g., CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
• In‑depth expertise with CPU/GPU architecture fundamentals, especially the memory subsystem.
• Domain expertise in high‑performance databases, ETL, data analytics, and/or vector database.
• Strong communication, organization, and prioritization skills, with a logical approach to problem solving.

• Experience optimizing/implementing database operators or query planners, especially for parallel or distributed frameworks (e.g., production database or Spark).
• Background with optimizing vector database index build and/or search.
• Experience profiling and optimizing CUDA kernels.
• Background with compression, storage systems, networking, and distributed computer architectures.

Data analytics is one of the rapidly growing fields in GPU‑accelerated computing. Traditional data engineering is CPU‑based and can be a bottleneck for machine learning and deep learning applications, which are highly optimized for GPUs. Many modern applications have complex data pipelines that can benefit from optimizations in memory management, compression, and parallel algorithms such as sort, search, join, aggregation, and scaling across multi‑GPU systems or many nodes.

Base salary range: $184,000–$287,500 for Level 4; $224,000–$356,500 for Level 5. Equity and benefits are also available.

Applications for this job will be accepted at least until October 26, 2025.

We are committed to fostering a diverse work environment and are proud to be an equal‑opportunity employer. Diversity is highly valued. We do not discriminate 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.