Senior Deep Learning Profiling Tools Engineer
US, CA, Santa Clara, United States
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NVIDIA
NVIDIA on grafiikkasuorittimen keksijä, jonka kehittämät edistysaskeleet vievät eteenpäin tekoälyn, suurteholaskennan.NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU-enabled deep learning ignited modern AI — the next era of computing — with the GPU acting as the workhorse that powers intelligent applications in a multitude of domains and computing environments. With performance at the center of everything we do at NVIDIA, we pride ourselves on not only building the world’s fastest processors, but also on providing a full ecosystem that empowers developers to realize that performance in practice.
NVIDIA’s Deep Learning Architecture and Libraries Group is looking for a software engineer to help us push the boundaries of our performance analysis capabilities. As a member of our team, you will work closely with GPU architects, CUDA developers, and deep learning performance engineers to devise innovative approaches to hardware and software profiling and incorporate them into our internal tools. Your work will accelerate progress toward our broader mission, which spans both hardware and software, to consistently deliver the world’s fastest accelerated computing systems in domains ranging from autonomous vehicles to supercomputers. Join our technically diverse team of GPU architects, software engineers, and infrastructure experts to advance the frontiers of computing performance!
What you’ll be doing:
Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms.
Design and develop tools, techniques and workflows for profiling and analysis of DL workloads
Work with multi-disciplinary teams to design, implement, and verify new features for profiling and monitoring, often incorporating new hardware capabilities
Define software/hardware metrics for performance analysis of DL workloads and verify them for upcoming architectures
Constantly learn about the latest techniques and frameworks for deploying and optimizing the performance of AI / DL workloads to improve the efficiency and effectiveness of our tools
What we need to see:
Bachelors, Masters, or PhD in relevant field (e.g. CS, EE, CE) or equivalent experience
8+ years of relevant experience (including graduate work if applicable)
Proficiency in C++ and Python.
Experience with deep learning Frameworks (e.g. PyTorch, JAX, TRT, ONNX, Triton) and strong understanding of deep learning fundamentals
Strong computer science fundamentals - algorithms, data structures, optimization, debugging, operating systems, and parallel computing
Ways To Stand Out From The Crowd:
Experience with performance analysis of AI training/inference applications
Knowledge of device drivers and/or compiler implementation
Knowledge of GPU and/or CPU architecture and general computer architecture principles
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 5, 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.Tags: Architecture Computer Science CUDA Deep Learning GPU JAX ONNX PhD Python PyTorch
Perks/benefits: Career development Equity / stock options
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