Job description
NVIDIA Math Libraries team is looking for a senior engineer to join our development efforts in the area of kernel generation for AI and HPC, specifically targeting matrix operations, JITing and fusions. Around the world, leading commercial and academic organizations are revolutionizing AI, scientific and engineering simulations, and data analytics, using data centers powered by GPUs. Applications of these technologies are in healthcare, NLP, VR, deep learning, autonomous vehicles and countless others. Did you know our team develops the GPU accelerated mathematical libraries that makes all of this possible?
What you will be doing:
Scoping, designing, and implementing high quality and performance numerical dense linear algebra software on GPUs.
Owning the execution of projects involving multiple engineers and sometimes teams.
Providing technical leadership and feedback to library engineers working with you on projects and sometimes mentor interns.
Working closely with product management and other internal and external customers to understand feature and performance requirements and contribute to the technical roadmaps of libraries.
Finding opportunities to improve library performance and reduce code maintenance overhead through re-architecting.
To be successful in your responsibilities which are by nature sophisticated, you will need to find and explain complex solutions, exercise leadership, and coordinate with multiple teams to work towards your goals.
What we need to see:
PhD, Master’s, or Bachelor's degree in Computer Science, Applied Math, or related science or engineering field of study (or equivalent experience).
8+ years of experience in designing, developing, testing, maintenance, and performance optimization of HPC software using C++.
Strong fundamentals in kernel generation and composable library design for linear algebra.
Leadership skills in driving software development projects.
Strong collaboration, communication, and documentation habits.
Kernel generation. JIT focus/experience desired
Ways to stand out from the crowd:
Experience with parallel programming, ideally using CUDA, MPI, OpenMP, OpenACC, pthreads.
Good understanding of Machine Learning and Deep Learning technologies as well as knowledge of GPU (preferred) or CPU hardware architecture.
Experience with low level programming using assembly for performance optimization and operator fusion is a huge plus.
Experience with agile software development practices using project management tools such as JIRA.
A scripting language, preferably Python.
With a competitive salary package and benefits, NVIDIA is 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. Are you a creative and autonomous GenAI Engineer, who loves challenges? Do you have a genuine passion for advancing the state of AI & machine learning across a variety of industries? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 12, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.