We are now looking for a Senior Deep Learning Performance Engineer!
Apply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.
Do you want to help drive the development of high-performance, power-efficient datacenter solutions for Large Language Models (LLMs)?
Do you have an interest in how system architecture across GPU, networking, CPU and IO relate to brand new generative AI capabilities?
Come join our team, and bring your experience and interests to help us optimize our next generation of datacenter hardware, deep learning frameworks and to redefine the deep learning industry once again.
What you'll be doing :
- Characterize a broad range of generative AI applications running on NVIDIA datacenters, based on their system characteristics.
- Find opportunities to improve efficiency across aspects ranging from CPU / GPU / System architecture to GPU Kernels and Libraries, and DL Frameworks.
- Develop analysis and lightweight profiling tools and methodologies to measure key performance metrics and to estimate potential for efficiency improvement.
- Work with key partners in Datacenter Design Teams, silicon IP Architecture Teams, as well as DL framework teams to evolve the balance of silicon resources for NVIDIA's next generation datacenters.
What we need to see :
- A Master’s degree in Electrical Engineering, Computer Science or Computer Engineering or equivalent experience. PhD is a plus.
- 6+ years of relevant work experience with exposure to any one of the two.
- System software development and performance analysis for parallel computing setups. Prior experience with performance aspects of Operating system intrinsics (e.
g. : Linux scheduling), GPU kernels (CUDA), or DL Frameworks (PyTorch, TensorFlow).
Silicon performance analysis of High Performance Computing or Deep Learning Systems with commonly used silicon performance monitoring and profiling tools (perf / gprof / nvidia-smi / dcgm).
In depth performance modeling experience in any one of CPU, GPU, Memory or Network Architecture is a plus.
- Proficiency in programming (Python, C / C++). Exposure to Containerization Platforms (docker) and Datacenter Workload Managers (slurm) would be viewed favorably.
- Knowledge of LLMs and their intrinsics is desired.
- Ability to plan, own and drive involved tasks from beginning to end, and to coordinate activities between team members.
Familiarity with multi-site teams or multi-functional teams is an added advantage.
NVIDIA invented the GPU in 1999 and over the years, fueled the growth of PC gaming, redefined computer graphics, and revolutionized parallel computing.
More recently, NVIDIA has orchestrated the development and adoption of culture-changing technologies in Artificial Intelligence and Cryptography.
Combining extraordinary graphics processors with innovative CPUs and pioneering networking technologies like Infiniband, NVIDIA has broken ground and set standards of excellence in an array of important and exciting applications.
As NVIDIA leads the industry in AI, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to system design.
We collaborate with a broad cross section of teams at NVIDIA ranging from DL research teams to CUDA Kernel and DL Framework development teams, to Silicon Architecture Teams.
As our team grows, and as we seek to identify and take advantage of long term opportunities, our needs are expanding as well.
With competitive salaries and a generous benefits package, 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 with us and, due to unprecedented growth, our best-in-class engineering teams are rapidly growing.
If you're a creative and autonomous engineer with a real passion for both silicon architecture and software performance and efficiency, we want to hear from you!
The base salary range is $176,000 - $333,500. 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.
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.
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