…As a member of our Hardware architecture deep learning team, you will contribute to features that help next-generation GPUs and systems advance the…

…As a member of our Hardware architecture deep learning team, you will contribute to features that help next-generation GPUs and systems advance the…

…Design and maintain detection systems including straggler node detection, GPU health signals, and fleet-level behavioral baselines. - Signal Calibration: Drive detection fidelity by reducing…

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and…

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and…

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and…

…computer vision workloads in GPU clusters. Deep understanding of petabyte-scale data architecture, including storage federation, high-throughput access, and data locality for AI…

…deep learning neural networks. Testing & Validation: Write comprehensive test suites, develop automated testing flows, and ensure zero regressions across different operating systems and hardware…

…architect, build, and deploy AI and Agentic solutions in production environments. You combine deep domain expertise in Generative AI, large-scale system design, and…

…GPUs, Neuron, TPU or other AI acceleration hardware, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems - Hands…

…deep learning workloads and related automation NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU…

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and…

…Experience with machine learning infrastructure, training systems, or model serving platforms. Deep understanding of performance engineering and systems optimization. Strong debugging and profiling skills…

…development and fleet learning. What you'll own System architecture & reliability - Design and evolve the platform's overall architecture for reliability, observability, and scalability…

…About the Work Design and develop sensor and compute systems for robotics Architect and/or deploy Nuro sensors & autonomous SW with high reliability and…

…About the Work Design and develop sensor and compute systems for robotics Architect and/or deploy Nuro sensors & autonomous SW with high reliability and…

…GPUs, Neuron, TPU or other AI acceleration hardware, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems - Hands…

…You will leverage Reinforcement Learning (RL), sim-to-real transfer, and other learning-based architectures to train policies that produce stable, dynamic gaits across…

…A day in the life A typical day as a Machine Learning Engineer involves architecting and building robust AI/ML infrastructure and intelligent systems…

…AI infrastructure architecture and model optimization — you will help customers understand hardware requirements and complexity (GPU, Trainium, networking), while also providing deep expertise in…

…focusing on onboard compute, perception, or planning systems. Experience with hardware accelerators (e.g., TPUs, GPUs) and ML models inference in edge/onboard environments…

…Model and Data Build large multi-modal generative world models that learn from robot experience, spanning model architecture, tokenization, and large-scale training and…

…experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware - Familiarity with recommendation systems is a bonus…

…systems that have been successfully delivered to customers, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and…

…Strong background in deep learning and neural networks, in particular training. Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture…