Senior Software Engineer, CUDA Deep Learning Systems

🕒 il y a 1 jour

🏄 California, Texas – Distant

🏄 California – Remote 🤠 Texas – Remote

💵 $184 000 - $356 500 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

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NVIDIA

Site WebLinkedInTous les Emplois

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

• Explore, research, and prototype systems optimizations for advanced deep learning models at the intersection of high-level deep learning frameworks and low-level CUDA through modeling, simulation, and silicon prototyping • Architect and optimize distributed computing systems from single-node to cluster-scale supercomputing environments • Design, implement, and optimize custom high-performance CUDA kernels for emerging neural network architectures and workloads • Analyze hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines • Collaborate with AI researchers, hardware and software architects, kernel and compiler authors, and CUDA driver experts to co-design systems and algorithms • Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms • Write clean, effective, and maintainable code and transition prototypes into open-source releases, framework integrations, internal tools, or commercial products

🎯 Exigences

• BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience • 8+ years of relevant industry experience or equivalent academic experience after degree achievement • Strong proficiency in C++ and Python programming • Solid background in deep learning fundamentals, with a focus on transformers • Strong understanding of distributed computing, multi-node scaling, and cluster-scale performance challenges • Proven experience in systems programming, computer architecture, and low-level systems performance optimization • Familiarity with GPU accelerator architectures • Hands-on experience with CUDA programming, kernel optimization, and workload profiling • Experience profiling and optimizing generative AI models, including large language models • Research background in machine learning systems or adjacent fields • Experience profiling and optimizing vision models, generative AI architectures, or diffusion models • Track record of initiative and willingness to deep-dive on problems across the stack • Preferred: expertise in performance internals and execution graphs of PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, or Megatron • Preferred: experience with NCCL, MPI, UCX, and distributed machine learning techniques such as pipeline, tensor, or expert parallelism • Preferred: knowledge of numerical methods and low-precision arithmetic such as NVFP4, MXFP4, FP8, or INT8 • Preferred: background in deep learning compilers and ML systems, including Triton, XLA, or torch.compile • Preferred: experience designing agentic AI systems for complex systems and infrastructure problems

🏖️ Avantages

• Equity • Benefits • Equal opportunity employer • Inclusive work environment