NVIDIA
Full TimeResearch and implement algorithms to optimize large language model inference for both low-latency and high-throughput scenarios, translating findings into production software. Requires an MSc/PhD in Computer Science or related field with at least five years of deep learning research experience, publications at top-tier conferences, and strong knowledge of LLM architectures. Essential skills include Python, PyTorch, and deep understanding of GPU performance optimization. Experience with inference systems like vLLM or TensorRT-LLM and large-scale GPU clusters is valued.
Written from this posting by Neural Jobs AI. The full description is below.
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.
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.
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 attitude, driven by the ambition to deliver solutions with real-world impact.
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.
We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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NVIDIA builds the GPUs and the CUDA software stack that most modern AI is trained and served on, along with its own research in graphics, robotics and foundation models.
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