Engineering Manager For Deep Learning Models
NVIDIA is seeking an engineering manager to lead engineering activities related to productizing Deep Learning models. Academic and commercial groups around the world are using GPUs to redefine Artificial Intelligence and data analytics, and to power data centers. Join the team building software which will be used by the entire world. Interact with the scientific community to implement and improve the latest algorithms. Ability to work in a multifaceted, product-centric environment is required and excellent interpersonal skills are also a requirement.
If you have a good understanding for deep learning and a strong algorithmic background, with exposure to large scale LLM / VLM deployment, inference optimization, and leadership experience, then this role may be a great one for you! In this role you will lead and mentor forward-thinking engineers and will own related activities and interactions with teams across NVIDIA. You will be working with key internal partners on priority alignment across relevant teams for roadmap development of highly optimized novel and state-of-the-art numerical, analytics, and deep learning algorithms and associated R&D duties. If the idea of pushing the boundaries of state-of-the-art research and development excites you, and are interested in getting exposure to the entire DL SW stack, come join the team that build the GPU-accelerated DL platform used by the entire world.
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Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 425,500 USD for Level 4. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 3, 2025. 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.
Learning Learning • Santa Clara, CA, US