Senior Deep Learning Research Engineer – Multimedia GPU team

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 closely with NVIDIA Research, hardware architecture teams, and product groups (such as NeMo, AI4Media, and 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 a culture of technical excellence, and maintain high standards via code and design reviews.

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 of working with Diffusion models, GANs, Transformers, VAEs, Neural Radiance Fields (NeRFs) / 3D Gaussian Splatting, GRUs etc.

Strong Programming & Software Architecture: Elite Python coding skills with a solid foundation in production-grade software design, scalability, and data structures.