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Tier-1 brand and metro location increase applicant density despite niche seniority.
Specialized generative-audio and GPU research limits cross-industry transferability.
Requires PhD, 10+ years, and specialized ML/GPU expertise, yielding very strict filters.
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Lead research, design, and development of advanced deep learning models for audio and speech AI problems.
Define technical vision and R&D strategy for NVIDIA’s future audio, speech, and multimedia deep learning algorithms aligned with hardware progress.
Train, optimize, and productize large-scale generative audio foundation models on distributed GPU clusters and edge NVIDIA platforms.
PhD in Computer Science, AI, Applied Mathematics or related quantitative field.
10+ years industry or post-doc experience developing deep learning models for audio, image, and video processing.
Expert-level hands-on experience with PyTorch and deep knowledge of multi-modal data pipelines including video and audio processing.
Elite Python programming skills and production-grade software architecture experience.
Established expert in generative AI architectures including Diffusion models, GANs, Transformers, and related deep learning techniques.
Experience leading large-scale distributed training of foundation models on GPU clusters using tools like Megatron-LM, DeepSpeed, PyTorch FSDP.
Proven record of impactful commercial AI product development or top-tier academic publications in multimedia AI domains.