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
Desirables
Experience in performance measurements and profiling
Experience with running large-scale workloads in HPC clusters
Knowledge and love for DevOps/MLOps practices
Solid understanding of Linux environments and containerization technologies
GPU programming experience is a plus
What the job involves
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
NVIDIA is a pioneer in accelerated computing, reshaping the industry with GPUs and data-center-scale offerings that drive AI innovations and power the metaverse.