Senior Deep Learning Engineer
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Job Description
Senior Deep Learning Engineer at NVIDIA focusing on optimizing and deploying AI models for high-performance inference on GPU platforms.
Responsibilities:
- Improve inference speed for Cosmos WFMs on GPU platforms.
- Effectively carry out the production deployment of Cosmos WFMs.
- Profile and analyze deep learning workloads to identify and remove bottlenecks.
Requirements:
- 8+ years of experience
- MSc or PhD in CS, EE, or CSEE or equivalent experience
- Strong background in Deep Learning
- Strong programming skills in Python and PyTorch
- Experience with inference optimization techniques (such as quantization) and inference optimization frameworks, one of: TensorRT, TensorRT-LLM, vLLM, SGLang
- Familiarity with deploying Deep Learning models in production settings (e.g., Docker, Triton Inference Server)
- CUDA programming experience
- Familiarity with diffusion models
- Proven experience in analyzing, modeling, and tuning the performance of GPU workloads, both inference and training.
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