Senior Solutions Architect, Data Processing

🕒 il y a 10 jours

🏄 California, Illinois, +2 états de plus – Distant

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💵 $184 000 - $356 500 / an

⏰ Temps Plein

🟠 Senior

💻 Ingénieur Solutions

🦅 Parrain de Visa H1B

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👻 Score fantôme 1%

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🗣️🇺🇸🇬🇧 Anglais requis

ETL

Spark

C++

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Logo of NVIDIA

NVIDIA

10 000+ employés

Fondée en 1993

🏥 Santé

🏭 Fabrication

🤖 Intelligence artificielle

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA est une entreprise technologique de premier plan, spécialisée dans le calcul accéléré et l’intelligence artificielle (IA). NVIDIA est à l’avant‑garde des avancées en GPU (processeurs graphiques), cloud computing, centres de données et réalité virtuelle, avec un accent particulier sur les secteurs du gaming, de l’automobile, de la santé et de la robotique. Ses innovations, telles que NVIDIA Omniverse, transforment les processus numériques traditionnels en permettant des simulations haute fidélité et des tâches de rendu de pointe. Ses applications couvrent de nombreux secteurs, des véhicules autonomes avec NVIDIA DRIVE aux solutions de santé avec NVIDIA Clara, ainsi que des analyses et workflows pilotés par l’IA.

Description

• Research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications • Work directly with technical experts from industry and academia to perform in-depth analysis and optimization of complex data-intensive workloads • Optimize performance for current GPU architectures • Influence the design of next-generation hardware architectures, software, and programming models • Collaborate with research, hardware, system software, libraries, and tools teams at NVIDIA • Influence industry and academic partners to advance data processing with NVIDIA’s product line

🎯 Exigences

• 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 • 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

🏖️ Avantages

• Equity • Benefits

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