About the role
We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the inference systems software stack! We build innovative AI systems software to accelerate for AI inference. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient attention kernel implementations, new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.
What you'll be doing:
Innovating and developing new AI systems technologies for efficient inference
Designing, implementing, and optimizing kernels for high impact AI workloads
Designing and implementing extensible abstractions for LLM serving engines
Building efficient just-in-time domain specific compilers and runtimes
Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
Contributing to open source communities like FlashInfer, vLLM, and SGLang
What we need to see:
Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred
2 + years (academic/ industry) experience with ML/DL systems development preferable
Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.
Strong Python and C/C++ programming skills
Ways to stand out from the crowd:
Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
Expertise in inference engines like vLLM and SGLang
Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cuTile, Triton, or similar)
Open source project ownership or contributions
You will also be eligible for equity and benefits.
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.Skills & Tags
Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
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