NVIDIA is searching for world-class research engineers to join the AI for Games team. If, like us, you are driven to pioneer AI research into real-life applications, we would love to talk to you! We are passionate about applications in multimodal generative AI, audio, video, language models, computer vision, and other areas, with the goal of improving graphics, gameplay, or other domains within the gaming and pro-visualization markets. You will collaborate with teams throughout the company to bring new AI features to market, as well as develop new AI features through your own work.What you'll be doing:
Research, design, and implement generative models that improve multi-modal language models with a focus on audio.
Use AI for solving product problems in gaming and other interactive experiences by designing techniques to adapt generative models to tasks, i.e. audio understanding and summarization.
Fine-tune multi-modal network architectures for optimal accuracy and inference speed; write optimal inference kernels for NVIDIA hardware.
Create prototypes to demonstrate real-life applications of your ideas and to accelerate productization.
Construct and curate large problem-specific datasets.
Keep up with the latest AI/DL research and collaborate with diverse teams (both internal and external to NVIDIA), including AI/DL researchers, hardware architects, and software engineers.
Participate in technology transfers to and from teams across NVIDIA.
What we need to see:
Master's in computer science/engineering, Machine Learning, AI, and related fields (or equivalent experience).
12+ years of machine learning / deep learning research or work experience.
Solid understanding of audio signal processing and natural language processing.
Excellent programming skills in C/C. Knowledge of parallel programming (i.e. CUDA and TensorRT) is a big plus.
Expertise with deep learning frameworks such as PyTorch.
A track record of proven research excellence via presentations, demos, or publications at leading venues such as GDC, ICCV/CVPR, NeurIPS, InterSpeech, ICASSP, SIGGRAPH etc. or other research artifacts such as software projects or significant product development.
Intelligent machines powered by AI computers that can learn, reason, and interact with people are no longer science fiction. Image recognition and speech recognition — GPU deep learning has provided the foundation for machines to learn, perceive, reason, and tackle problems. The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for deep learning, and NVIDIA is known as “the AI computing company.”With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.The base salary range is 220,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/) . NVIDIA accepts applications on an ongoing basis. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.