Perfilarás, analizarás y optimizarás cargas de trabajo de entrenamiento e inferencia de aprendizaje profundo en hardware GPU y en la pila de software de DL, además de construir herramientas para automatizar este trabajo. También orientarás a investigadores e ingenieros de NVIDIA en la mejora del rendimiento de las cargas de trabajo.
Modalidad
Presencial
Nivel
Senior
Experiencia
5+ años
Skills
Deep LearningPyTorchCUDAC++
Python
GPU Architecture
Performance Profiling
TensorRT-LLM
vLLM
Neural Networks
Performance Modeling
OpenCL
Sobre el puesto
We are now looking for a Senior DL Algorithms Engineer! NVIDIA is seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning training, one of today's most essential workloads in the world. If you are unafraid to work across all layers of the hardware/software stack, from GPU architecture to Deep Learning Framework, to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution while helping deep learning users around the globe enjoy ever-higher training speeds. What you will be doing: Understand, analyze, profile, and optimize deep learning training and inference workloads on state-of-the-art hardware and software platforms. Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the performance of workloads. Implement production-quality software across NVIDIA's deep learning platform stack. Build tools to automate workload analysis, workload optimization, and other critical workflows. What we want to see: 5+ years of experience. MSc or PhD in CS, EE or CSEE or equivalent experience. Strong background in deep learning and neural networks, both training & inference. Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. Proven experience analyzing, modeling and tuning application performance. Programming skills in C++ and Python. Ways to stand out from the crowd: Experience with modern LLM inference frameworks (TRT-LLM, vLLM, Ollama, etc.) Strong fundamentals in algorithms. Experience with production deployment of Deep Learning models. Proven experience with processor and system-level performance modelling. GPU programming experience (CUDA or OpenCL) is a strong plus but not required. As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing data center deployments and establishing a data-driven approach to hardware design and system software development. 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 skills needs are growing as well. 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 on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.
