Senior Solutions Architect, Data Processing

at Nvidia

📍 World
📍 Canada
📍 United States

USD 184,000-287,500 per year

SENIOR

✅ Remote

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ^?

Spark @ 4 ETL @ 4 GitHub @ 4 Algorithms @ 7 Communication @ 4 Networking @ 4 Parallel Programming @ 4 Prioritization @ 4 CUDA @ 4 GPU @ 4

Details

NVIDIA is seeking a Solutions Architect for high-performance databases who will research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications. The role involves in-depth analysis and optimization of complex data-intensive workloads, influencing hardware and software design, and collaborating with industry and academic partners to advance data processing on NVIDIA platforms.

Responsibilities

Research and develop techniques to GPU-accelerate high-performance databases, ETL, and data analytics applications.
Work directly with technical experts in industry and academia to analyze and optimize complex data-intensive workloads for 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 product line.

Requirements

Masters or PhD in Computer Science, Computer Engineering, or 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 (examples: CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB).
In-depth expertise with CPU/GPU architecture fundamentals, especially the memory subsystem.
Domain expertise in high-performance databases, ETL, data analytics and/or vector databases.
Good communication and organization skills; logical problem-solving and prioritization.

Ways to stand out

Experience optimizing/implementing database operators or query planners, especially for parallel or distributed frameworks (e.g., production databases 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.

Additional information & benefits

Data Analytics is a rapidly growing field in GPU-accelerated computing; many data preprocessing and engineering pipelines can benefit from GPU optimizations across memory management, compression, parallel algorithms (sort, search, join, aggregation, groupby), multi-GPU scaling, and multi-node scaling.
Examples of related open-source projects mentioned: https://github.com/rapidsai/cudf/, https://github.com/NVIDIA/nvcomp, https://github.com/rapidsai/distributed-join, https://github.com/NVIDIA/cuCollections
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.
You will also be eligible for equity and benefits: https://www.nvidia.com/en-us/benefits/
Applications for this job will be accepted at least until July 29, 2025.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. The company does not discriminate on the basis of legally protected characteristics.