NVIDIA
Senior Solutions Architect, Data Processing
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Senior Solutions Architect, Data Processing
role at
NVIDIA
What You Will Be Doing
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 to ensure the best possible performance of 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.
What We Need To See
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, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
Domain expertise in high performance databases, ETL, data analytics and/or vector database.
Good communication and organization skills, with a logical approach to problem solving and prioritization skills.
Ways To Stand Out From The Crowd
Experience optimizing/implementing database operators or query planner, 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. Data preprocessing and data engineering are traditionally CPU based and are becoming the bottleneck for Machine Learning (ML) and Deep Learning (DL) applications, as performance of the frameworks and core ML/DL libraries has been highly optimized leveraging GPUs. Many of today’s applications have complex data analytics pipelines that can benefit from optimizations in memory management, compression, parallel algorithms like sort, search, join, aggregation, groupby, scaling up to multi‑GPU systems, and scaling out to many nodes. Take a look at some of the open-source projects that NVIDIA employees have worked on: RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed join, 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 for Level 4, and $224,000 USD – $356,500 USD for Level 5.
Applications for this job will be accepted at least until October 26, 2025.
You will also be eligible for equity and benefits.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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
What You Will Be Doing
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 to ensure the best possible performance of 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.
What We Need To See
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, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
Domain expertise in high performance databases, ETL, data analytics and/or vector database.
Good communication and organization skills, with a logical approach to problem solving and prioritization skills.
Ways To Stand Out From The Crowd
Experience optimizing/implementing database operators or query planner, 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. Data preprocessing and data engineering are traditionally CPU based and are becoming the bottleneck for Machine Learning (ML) and Deep Learning (DL) applications, as performance of the frameworks and core ML/DL libraries has been highly optimized leveraging GPUs. Many of today’s applications have complex data analytics pipelines that can benefit from optimizations in memory management, compression, parallel algorithms like sort, search, join, aggregation, groupby, scaling up to multi‑GPU systems, and scaling out to many nodes. Take a look at some of the open-source projects that NVIDIA employees have worked on: RAPIDS cuDF, NVIDIA nvcomp, NVIDIA Distributed join, 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 for Level 4, and $224,000 USD – $356,500 USD for Level 5.
Applications for this job will be accepted at least until October 26, 2025.
You will also be eligible for equity and benefits.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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