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Senior Deep Learning Research Engineer – Multimedia GPU team

NVIDIA· Engineer, Sys SW
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Hybrid (Bengaluru), Hybrid (Pune)full-timePosted 3mo ago

About the role

Senior position bridging deep learning research and production in multimedia AI, focusing on audio foundation models, generative AI, and multi-modal processing with edge deployment and collaboration across NVIDIA Research, hardware, and product groups.

Responsibilities

  • Pioneer Generative AI - Audio Architecture: Lead the research, design, and development of state-of-the-art deep learning models solving complex problems in audio and speech domains.
  • Drive Future Technology Roadmaps: Define the technical vision and R&D strategy for NVIDIA’s future Audio, Speech and multimedia DL algorithms, ensuring alignment with hardware advancements.
  • Scale Massive Foundation Models: Train and optimize large-scale generative models (Diffusion, Transformers, Autoregressive models) using distributed training across massive GPU clusters.
  • Audio-Speech-Visual Fusion: Develop advanced algorithms for speech transformation, spatial audio, audio enhancements, and real-time video/audio enhancements using Deep Learning Algos.
  • Cross-Functional Leadership: Collaborate with NVIDIA Research, hardware architecture teams, and product groups (NeMo, AI4Media, Broadcast) to productize breakthrough technologies.
  • Productize and Deploy models on Edge: Develop and productize inference models on NVIDIA GPUs and Nvidia RTX Spark platforms as SDK/Microservices after optimization.
  • Technical Mentorship: Mentor senior engineers and scientists, foster technical excellence, and maintain high standards via code and design reviews.

Qualifications

  • PhD in Computer Science, Artificial Intelligence, Applied Mathematics, or a related quantitative field.
  • 10+ years of industry or post-doc experience directly developing advanced deep learning models for audio, image, and video processing.
  • Deep Mastery of Generative AI: Proven track record with Diffusion models, GANs, Transformers, VAEs, NeRFs / 3D Gaussian Splatting, GRUs, etc.
  • Strong Programming & Software Architecture: Elite Python coding skills with production-grade software design, scalability, and data structures.
  • Framework Proficiency: Expert-level PyTorch and strong experience with multi-modal data processing pipelines (video decoding, audio DSP, spectrogram analysis).
  • Proven Impact: Portfolio of shipped commercial AI products or strong publication record at top AI conferences (CVPR, ICCV, SIGGRAPH, NeurIPS, ICASSP, Interspeech).

Skills

Required:PhD-level expertise in AI/MLDeep learning model developmentPythonPyTorch
Nice to have:C++/GPU optimization

Benefits

  • Not specified in description
Last updated Jul 3, 2026. Interested? Apply on the company site.

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