Performance optimization, analysis, and tuning of LLM, VLM and GenAI models for DL inference, serving and deployment in NVIDIA/OSS LLM frameworks
Scale performance of LLM models across different architectures and types of NVIDIA accelerators
Scale performance for max throughput, minimum latency and throughput under latency constraints
Contribute features and code to NVIDIA/OSS LLM frameworks, inference benchmarking frameworks, TensorRT, and Triton
Work with cross-collaborative teams across generative AI, automotive, image understanding, and speech understanding to develop innovative solutions

Requirements

Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Engineering, Computer Science, EECS, AI)
2+ years of relevant software development experience
Excellent Python/C/C++ programming, software design and software engineering skills
Experience with a DL framework like PyTorch, JAX, TensorFlow
Prior experience with a LLM framework or a DL compiler in inference, deployment, algorithms, or implementation
Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application
Architectural knowledge of CPU and GPU
GPU programming experience (CUDA or OpenCL)

Benefits

Equity
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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonCC++Deep LearningPyTorchJAXTensorFlowCUDAOpenCLperformance optimization

Soft Skills

collaborationcommunicationproblem-solvinginnovation

Certifications

Bachelor's degreeMaster's degreePhD