Senior Deep Learning Performance Engineer - Training at Scale

October 28

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NVIDIA

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GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Description

• Implement deep learning models from multiple data domains (CV, NLP/LLMs, ASR, TTS, RecSys and others) in multiple DL frameworks (PyT, JAX, TF2, DGL and others) • Implement and test new SW features (Graph Compilation, reduced precision training) that use the most recent HW functionalities. • Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms. • Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the design, usability and performance of workloads. • Lead best-practices for building, testing, and releasing DL software.

Requirements

• 5+ years of experience in DL model implementation and SW Development • BSc, MS or PhD degree in Computer Science, Computer Architecture, Mathematics, Physics or related technical field or equivalent experience • Excellent Python programming skills, extensive knowledge of at least one DL Framework • Strong problem solving and analytical skills • Algorithms and DL fundamentals • Experience in performance measurements and profiling • Experience with running large-scale workloads in HPC clusters • Knowledge and love for DevOps/MLOps practices for Deep Learning-based product’s development. • Solid understanding of Linux environments and containerization technologies such as Docker • GPU programming experience (CUDA or OpenCL) is a plus but not required.