[Remote] Solutions Architect, Data Processing - New College Grad 2026

Note: The job is a remote job and is open to candidates in USA. NVIDIA is a leading technology company known for its innovation in GPU technology and AI. They are seeking a New College Grad Solutions Architect to research and develop techniques for GPU-accelerating high-performance databases and data analytics applications, collaborating with technical experts to optimize performance and influence future hardware designs.

Responsibilities

• Research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications
• Work directly with other technical experts in their fields (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

Skills

• Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent 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
• Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark)
• Background in optimizing vector database index build and/or search
• Experience profiling and optimizing CUDA kernels
• Background with compression, storage systems, networking, and distributed computer architectures

Benefits

• Equity
• Benefits

Company Overview

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