NVIDIA
Senior Solutions Architect, Data Processing
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Senior Solutions Architect, Data Processing
role at
NVIDIA .
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, investigating hardware and system bottlenecks, and optimizing performance of data‑intensive applications, this is the opportunity for you. The Solution Architecture Team invites you to consider this role, where you will work on the cutting edge of technology with visibility and impact at a global leader like NVIDIA.
NVIDIA has reinvented itself over two decades, starting with the GPU in 1999 that sparked the PC gaming market, revolutionized parallel computing, and ignited modern AI. NVIDIA is a learning machine that adapts to new opportunities and solves problems that matter to the world. Our mission is to amplify human imagination and intelligence. Join our team today!
What You Will Be Doing
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 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 industry and academic partners to push the bounds of data processing with NVIDIA’s full product line.
What We Need To See
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 memory subsystems.
Domain expertise in high‑performance databases, ETL, data analytics, and/or vector databases.
Good communication and organization skills, with a logical approach to problem solving and prioritization.
Ways To Stand Out From The Crowd
Experience optimizing or 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 a rapidly growing field in GPU‑accelerated computing. Data preprocessing and engineering are traditionally CPU‑based and can become bottlenecks for Machine Learning (ML) and Deep Learning (DL) applications. NVIDIA’s open‑source projects—RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed Join, NVIDIA cuCollections—demonstrate our work in this area.
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 for Level 4, and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2025.
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal‑opportunity employer. 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.
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Senior Solutions Architect, Data Processing
role at
NVIDIA .
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, investigating hardware and system bottlenecks, and optimizing performance of data‑intensive applications, this is the opportunity for you. The Solution Architecture Team invites you to consider this role, where you will work on the cutting edge of technology with visibility and impact at a global leader like NVIDIA.
NVIDIA has reinvented itself over two decades, starting with the GPU in 1999 that sparked the PC gaming market, revolutionized parallel computing, and ignited modern AI. NVIDIA is a learning machine that adapts to new opportunities and solves problems that matter to the world. Our mission is to amplify human imagination and intelligence. Join our team today!
What You Will Be Doing
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 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 industry and academic partners to push the bounds of data processing with NVIDIA’s full product line.
What We Need To See
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 memory subsystems.
Domain expertise in high‑performance databases, ETL, data analytics, and/or vector databases.
Good communication and organization skills, with a logical approach to problem solving and prioritization.
Ways To Stand Out From The Crowd
Experience optimizing or 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 a rapidly growing field in GPU‑accelerated computing. Data preprocessing and engineering are traditionally CPU‑based and can become bottlenecks for Machine Learning (ML) and Deep Learning (DL) applications. NVIDIA’s open‑source projects—RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed Join, NVIDIA cuCollections—demonstrate our work in this area.
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 for Level 4, and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2025.
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal‑opportunity employer. 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.
#J-18808-Ljbffr