76 to 100 of 108 Permanent CUDA Jobs

deep learning models in PyTorch (not just using high-level tooling).Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly.Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level ...

/SL algorithms drawn from the latest literature Rapidly prototype in Python/JAX/PyTorch, then port to embedded C++/CUDA Develop Physics-Based Autonomy to perform Mission Planning & Decision-Making Apply supervised learning, reinforcement learning, and other AI/ML techniques to high-fidelity astrodynamics planning … practices and standards Experience in simulation development for space vehicle applications Experience in Embedded Software, Space Flight Software, or Simulation Software Experience with Python, CUDA, C/C++ programming Preferred Qualifications: Current/Active TS/SCI MS or PhD in Computer Science or Reinforcement Learning, or STEM degree ...

system installation, performance tuning, and troubleshootingExpertise in troubleshooting distributed GPU workloadsDeep knowledge around GPU optimization and performance Proficiency in Python scripting and automation frameworks CUDA or C/C++ experience is a plusExperience with NVIDIA technologies beyond CUDA, such as NCCL, GPUDirect RDMA, and NVLink Familiarity with configuration ...

resources. Integrate ML models into production systems where latency matters. Work across a mix of programming languages: C/C++/Python/CUDA and other low-level GPU languages. Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle … Proficiency in Pytorch, JAX, Tensorflow or other DL library. Ability to thrive in a collaborative, team-oriented environment Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent) Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference ...

resources. Integrate ML models into production systems where latency matters. Work across a mix of programming languages: C/C++/Python/CUDA and other low-level GPU languages. Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle … Proficiency in Pytorch, JAX, Tensorflow or other DL library. Ability to thrive in a collaborative, team-oriented environment Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent) Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference ...

building on NVIDIA technologies, evaluating technical maturity and platform alignment. You will work with venture capital and NVIDIA teams to accelerate production adoption of CUDA libraries and SDKs, deliver technical workshops, and support startups across Europe. Travel to engage with startups and investors is expected. #J-18808-Ljbffr ...

Inference Engineer to define and build how we serve AI workloads at scale, reporting to the CTO. You’ll own the layer above CUDA/GPU work, shaping inference delivery, throughput, and reliability as we scale data-centre compute for energy applications. With 4+ years in large-scale inference ...

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high-stakes industries like finance, manufacturing, defense, healthcare, and ...

systems, storage, fabric, MLOps stack and managed services — to land service-led AI solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA AI Enterprise, Run:ai, Slurm, Kubernetes/Kubeflow) and managed-service operating models across multiple domains, delivery units and geographies. …/NVSwitch fabrics, congestion control and fabric design for rail-optimised and fat-tree topologies. Working knowledge of the AI software and orchestration stack: CUDA, cuDNN, NCCL, ROCm, Triton Inference Server, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes (with GPU Operator), Kubeflow, Run:ai, MLflow and NVIDIA AI Enterprise. Familiarity ...

systems, storage, fabric, MLOps stack and managed services — to land service-led AI solutions. Lead integration of compute, storage, networking, the AI software stack (CUDA, ROCm, Triton, NIM, NVIDIA AI Enterprise, Run:ai, Slurm, Kubernetes/Kubeflow) and managed-service operating models across multiple domains, delivery units and geographies. …/NVSwitch fabrics, congestion control and fabric design for rail-optimised and fat-tree topologies. Working knowledge of the AI software and orchestration stack: CUDA, cuDNN, NCCL, ROCm, Triton Inference Server, NIM, vLLM, TensorRT-LLM, Slurm, Kubernetes (with GPU Operator), Kubeflow, Run:ai, MLflow and NVIDIA AI Enterprise. Familiarity ...

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical ...

Research Engineer Cambridge or London, UK (100% Onsite) Our client is a global leader in semiconductor innovation, developing advanced technologies that power billions of smart devices worldwide. With significant investment in artificial intelligence research, the ...

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and ...

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and ...

strategy, cloud accelerator economics, or GPU fleet cost management.Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems.Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues.Experience with Rust, C++, Go, CUDA, or other systems languages used for performance ...

accelerator economics, or GPU fleet cost management. Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems. Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues. Experience with Rust, C++, Go, CUDA, or other systems languages used ...

advancing AI and engineering best practices. Day-to-day tasking can include: Working on high-throughput vision systems on NVIDIA Jetson hardware, involving; CUDA/TensorRT acceleration Multi-modal (thermal + optical) sensors Robust real-time tracking Exploring AI Assurance and AI Safety Delivering technical expertise on a variety … Skills: We are interested in the following skills, but they are not essential for you to apply: Knowledge of C++, Python, PyTorch, OpenCV, CUDA, TensorRT, Git, WSL, Docker, Jira/Confluence Machine Learning and Deep Learning Computer Vision methodologies and algorithms MLOps Developing AI for use on Edge Computers ...

engineers who have:A track record of working on model training or model inference at scale, or on low‐level GPU coding (e.g. CUDA, Triton). Experience with one is great, multiple is even better.What will I be doing As a Senior AI Infrastructure Engineer focused on model training … following:Model training (especially transformers and LLMs).Model inference at scale (again, especially transformers and LLMs).Low‐level GPU work, such as writing CUDA or Triton kernels.Comfortable working in production environments at meaningful scale (traffic, data, or organizational).You communicate clearly, can explain complex technical topics to different audiences ...

good understanding of scientific policy engagement, grant processes, or national/European research program structures.Experience with NVIDIA's AI software stack, powered by CUDA and CUDA-X libraries, e.g. NVIDIA AI Enterprise, NeMo Framework, Megatron Bridge, NIM, TensorRT-LLM, Dynamo, NeMo Agent Toolkit, and Triton Inference Server ...

scientific policy engagement, grant processes, or national/European research program structures. Experience with NVIDIA's stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec ...

scientific policy engagement, grant processes, or national/European research program structures. Experience with NVIDIA's stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec ...

data centre systems: low-level performance engineering for large-scale compute clusters, tying GPU workload behaviour to energy availability and grid demand. This puts CUDA/GPU performance engineering at the centre of how Fuse scales its compute infrastructure.ResponsibilitiesDesign, implement, and optimise CUDA kernels for high-throughput, latency … against CPU/GPU baselines and drive continuous performance improvementsContribute to internal libraries, documentation, and best practices for GPU performance engineeringRequirements4+ years writing production CUDA code, or equivalent strong project/industry experienceDeep understanding of GPU architecture (SMs, warps, memory hierarchy, occupancy)Proficiency in C++ and CUDA; experience ...

containerd, Helm, Operators; debugging pods, DaemonSets, CSI, CNI, and ingress/load balancers).Demonstrated experience operating GPU‐accelerated workloads in production:NVIDIA GPUs, drivers, CUDA concepts, GPU utilization/perf triageNVIDIA GPU Operator and Kubernetes‐based GPU lifecycle managementFamiliarity with DGX/HGX or similar GPU cluster platforms.Practical experience … Enterprise components and toolchain, for example:NVIDIA NIM inference microservicesNVIDIA NeMo framework/NeMo Retriever/NeMo CuratorTriton Inference Server, TensorRT/TensorRT‐LLM, CUDA librariesNVIDIA blueprints for enterprise RAG and agentic AI.Experience designing, operating, or supporting MLOps/GenAI pipelines: CI/CD for models, deployment strategies, canarying ...

impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions.QualificationsStrong engineering skills, especially any of: CUDA/Triton/Pallas/CuTe DSL kernel development, lower-level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experienceMust ...

business, and it will be challenging: this is a field with no easy or obvious solutions. QualificationsStrong engineering skills, especially any of: CUDA/Triton/Pallas/CuTe DSL kernel development, lower-level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experienceMust have ...