NVIDIA, a leader in AI and high-performance computing, seeks a Senior Deep Learning Research Engineer for its Multimedia GPU team. This role involves pioneering next-generation audio foundation models and addressing complex, multi-modal AI challenges. Join us to redefine industry standards in entertainment, communication, and digital twins.

This position is instrumental in bridging the gap between cutting-edge deep learning research and production-ready solutions. You will be at the forefront of developing technologies that will shape the future of spatial computing and generative AI within multimedia applications.

Lead the research and development of advanced deep learning models for audio and speech. Drive technical roadmaps and R&D strategies for NVIDIA's multimedia DL algorithms, aligning with hardware advancements. Train and optimize large-scale generative models using distributed GPU clusters. Develop algorithms for speech transformation, spatial audio, and real-time video/audio enhancements. Collaborate across NVIDIA Research, hardware teams, and product groups to productize breakthrough technologies. Optimize and deploy inference models on NVIDIA GPUs and RTX Spark platforms.

Provide technical mentorship to senior engineers and scientists, fostering a culture of excellence. Ensure high standards are maintained through rigorous code and design reviews. Contribute to productizing and deploying models as SDKs or microservices after optimization.

A PhD in Computer Science, Artificial Intelligence, Applied Mathematics, or a related quantitative field is required. A minimum of 10 years of industry or post-doc experience in developing advanced deep learning models for audio, image, and video processing is essential.

Demonstrate deep mastery of Generative AI, including Diffusion models, GANs, Transformers, and VAEs. Possess elite Python coding skills with a strong foundation in production-grade software design and scalability. Exhibit expert-level hands-on experience with PyTorch and familiarity with multi-modal data processing pipelines. A strong portfolio of shipped AI products or a stellar publication record at top AI conferences is highly valued.