Senior Deep Learning Research Engineer – Multimedia GPU Team

About the Role

NVIDIA, a global frontrunner in AI, high-performance computing, and visualization, employs GPU technologies across diverse domains such as modern computing, robotics, autonomous systems, and the metaverse. As pioneers in AI computing, NVIDIA is actively shaping the future in multimedia, generative AI, and spatial computing.

We seek an insightful Senior Deep Learning Research Engineer to join our Multimedia GPU team. This role involves bridging advanced deep learning research with production, focusing on next-generation audio foundation models. Candidates passionate about tackling highly complex multi-modal AI challenges that redefine standards in entertainment, communication, and digital twin applications are encouraged to apply.

Key Responsibilities

• Lead the research, design, and implementation of cutting-edge deep learning architectures specifically targeting audio and speech applications.
• Establish and execute the technical vision and R&D strategy for NVIDIA’s future multimedia deep learning algorithms, harmonizing with hardware upgrades.
• Develop and optimize large-scale generative AI models—including Diffusion, Transformers, and Autoregressive types—utilizing distributed training on extensive GPU clusters.
• Create sophisticated algorithms for audio-speech-visual fusion tasks like speech transformation, spatial audio processing, audio enhancement, and real-time video/audio enhancement via deep learning techniques.
• Collaborate across teams including NVIDIA Research, hardware architects, and product groups like NeMo and AI4Media to translate research innovations into deployable technologies.
• Engineer and deploy inference-ready models optimized for edge devices using NVIDIA GPUs and RTX Spark platforms, delivered as SDKs or microservices.
• Provide technical mentorship to senior engineers and scientists, enforcing high standards through rigorous code and design reviews.

Qualifications & Experience

• PhD degree in Computer Science, Artificial Intelligence, Applied Mathematics, or a closely related field.
• Over 10 years of professional or post-doctoral experience in advanced deep learning model development for audio, image, and video processing applications.
• Expertise in generative AI approaches such as Diffusion models, GANs, Transformers, VAEs, Neural Radiance Fields/3D Gaussian Splatting, and GRUs.
• Excellent Python programming skills coupled with strong background in scalable, production-quality software architecture and data structures.
• Proficient with PyTorch framework and extensive experience in multi-modal data pipeline handling (including video decoding, audio digital signal processing, and spectrogram analysis).
• Documented impact via successful deployment of high-profile commercial AI products or a significant publication record at leading AI conferences like CVPR, ICCV, SIGGRAPH, NeurIPS, ICASSP, Interspeech.

Preferred Skills

• In-depth knowledge of generative audio/speech architectures and associated algorithms.
• Experience with large-scale distributed training frameworks such as Megatron-LM, DeepSpeed, or PyTorch FSDP on cluster systems.
• Strong command of C++ and low-level GPU optimization tools including CUDA, cuDNN, Triton, and TensorRT.
• Experience in constructing world models or physics-informed neural networks for video synthesis is advantageous.

Equal Employment Opportunity

NVIDIA is devoted to maintaining an inclusive workplace environment and is an equal opportunity employer. Discrimination based on race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability, or other legally protected categories is not tolerated.