NVIDIA
SeniorDeepLearningResearcher,LLMInference
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optimal for Senior candidates.
“Senior Deep Learning Researcher, LLM Inference at NVIDIA. Skills: Deep learning research, LLM inference, Algorithm invention and implementation. Research, invent, and implement groundbreaking algorithms for LLM inference. Translate research into practical software solutions”
What You'll Achieve.
Advance the state of the art in both low-latency and high-throughput scenarios; Directly impact NVIDIA's products and customers; Drive the development of advanced inference technologies; Establish NVIDIA as the definitive platform for high-performance LLM inference; Make the latest LLMs more efficient and accessible for users worldwide
Industry & Context.
Problem-solving mentality; Identify bottlenecks and opportunities for algorithmic optimizations
What They're Looking For.
Must Have
MSc/PhD in Computer Science, Electrical Engineering, or a closely related field, At least 5 years of relevant experience in deep learning research or applied research, Publications in a top-tier AI/ML conference (e. g. , NeurIPS, ICLR, ICML), Deep understanding of LLM architectures coupled with hands-on experience in training large-scale models, Excellent programming skills, particularly in Python and deep learning frameworks like PyTorch, Experience with software engineering standards, A problem-solving mentality and a proactive attitude, driven by the ambition to deliver solutions with real-world impact
Nice to Have
Hands-on research experience in LLM inference optimization algorithms such as speculative decoding or parallelization strategies, Proven experience with High-Performance Computing (HPC) environments, including training or running inference on large-scale GPU clusters (tens to hundreds of GPUs), Deep familiarity and experience with popular LLM inference systems (e. g. , vLLM, TensorRT-LLM), Experience from a world-class industrial research group or a top-tier institution
What You'll Do.
and implement groundbreaking algorithms for LLM inference
Translate research into practical software solutions
Analyze the performance of new algorithms on NVIDIA’s latest hardware
Identify bottlenecks and opportunities for algorithmic optimizations
How You'll Work.
Team & Collaboration
Collaborate with internal research, engineering, and product teams across the globe; Engage with skilled problem-solvers at NVIDIA and top organizations; Partner with leading scientific organizations and industry pioneers
Full Job Description
We are seeking a highly motivated Senior Deep Learning Researcher to join our team! This is an outstanding opportunity to conduct impactful research and develop the next generation of large language model (LLM) inference algorithms. You will work on technologies that directly enhance NVIDIA's software, making the latest LLMs more efficient and accessible for users worldwide. By joining us, you will be part of a strategic effort to establish NVIDIA as the definitive platform for high-performance LLM inference. You will engage with skilled problem-solvers at NVIDIA and top organizations, crafting AI technology advancements. ## **What you 'll be doing:** * Research, invent, and implement groundbreaking algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios. * Translate research into practical software solutions that directly impact NVIDIA's products and customers. * Collaborate with internal research, engineering, and product teams across the globe to drive the development of advanced inference technologies. * Analyze the performance of new algorithms on NVIDIA’s latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations. * Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications. ## **What we need to see:** * MSc/PhD in Computer Science, Electrical Engineering, or a closely related field. * At least 5 years of relevant experience in deep learning research or applied research. * Publications in a top-tier AI/ML conference (e.g., NeurIPS, ICLR, ICML). * Deep understanding of LLM architectures coupled with hands-on experience in training large-scale models. * Excellent programming skills, particularly in Python and deep learning frameworks like PyTorch, and experience with software engineering standards. * A strong problem-solving mentality and a proactive
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