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NVIDIA AI
Senior Deep Learning Research Engineer – Multimedia GPU team
NVIDIA AI
Pune•On-site•10-13 Yrs•Jul 1
Job description
Overview
We are looking for a visionary Senior Deep Learning Research Engineer to join our team.
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 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.
- Framework Proficiency: Expert-level hands-on experience with PyTorch and deep familiarity with multi-modal data processing pipelines (video decoding, audio DSP, spectrogram analysis).
- Proven Impact: A strong portfolio of shipped high-impact commercial AI products or a stellar publication record at top-tier AI conferences (CVPR, ICCV, SIGGRAPH, NeurIPS, ICASSP, Interspeech).
- Deep understanding of Generative Audio/Speech Architecture and Algorithms
Qualifications
- High proficiency in C++ and low-level GPU optimization tools like CUDA, cuDNN, Triton, or TensorRT.
- NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.