51 to 75 of 140 Permanent CUDA Jobs

understanding of IEC 60601-1-8 or equivalent safety standards, experience with state-machine-driven supervisors and fault-management systems, experience with NVIDIA Jetson, CUDA or GPU-accelerated processing, experience with Yocto and embedded Linux board-support packages, experience with systemd, sd_notify, D-Bus and journald, experience with ...

reasoning, collaboration, and communication with trading researchers. Intellectual curiosity, originality, practical judgement, and reliable availability. Useful experience: high-performance computing, distributed large-model training, CUDA or ROCm optimisation, end-to-end model development, and ML research/tooling/infrastructure best practices. International candidates are encouraged to apply. Jump ...

understanding of packaging, type checking, and performance profiling. APIs : Proficiency in gRPC/Protobuf and REST for cross-language integration. Performance Optimization : GPU acceleration (CUDA/cuDNN), mixed precision, XLA, profiling. Observability : Metrics, tracing, structured logging, dashboards. Security : SBOM, image signing, role-based access, vulnerability scanning. Preferred Qualifications Experience ...

forecasting tools, Python or spreadsheet-based, from research, a thesis, a placement, or serious personal projects Hands-on work with GPU or accelerator code, CUDA or similar Familiarity with profiling tools (Nsight, PyTorch Profiler) and ideally some exposure to monitoring stacks (Prometheus, Grafana) Strong Python for data work, Pandas ...

range of hardware from resource constrained embedded systems through to cloud computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc). Your future colleagues will be similarly highly skilled, with experience across industry and the drive to innovate. You will find yourself ...

throughput distributed systems Background in AI media generation (image, video, audio) Experience building internal ML tooling or developer-facing APIs Experience with kernels in CUDA/C++ We're a remote-first team that comes together in person twice a year to plan, collaborate, and celebrate wins. ...

skills: Extensive experience in building AI platforms covering model hosting/inference optimisation and fine-tuning pipelines (LLM experience strongly preferred) Strong Python and CUDA engineering; solid understanding of GPU/CPU architecture and HPC fundamentals Deep inference optimisation expertise: KV-cache, batching, quantisation (INT4/FP8/GPTQ ...

Experience with developing serving infrastructure. Experience programming hardware accelerators (GPUs, TPUs) via ML frameworks (e.g., JAX, PyTorch) or low-level programming models (e.g., Pallas, CUDA, OpenCL). Experience profiling software to identify performance bottlenecks. Experience with distributed ML systems optimization and parallelism (e.g., data, model, or pipeline parallelism). ...

finance, trading, or quantitative research (not required). Publications, competition results (e.g., Kaggle, academic ML contests), or open-source contributions. Familiarity with C++, CUDA, or low-latency systems. Here is why you should join our dynamic team: Opportunity to work at one of the world's leading algorithmic trading ...

these — as long as you're open to learning, Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London ...

these — as long as you're open to learning. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London ...

these. As long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture: the team works from our London ...

range widely, and include: Scientific tools Embedded C/C++ (typically owned by dedicated firmware engineers, but software engineers are welcome to learn!) Linux, CUDA, Server engineering for our AI safety, - security, and verification work Custom simulation software (usually python) Data analysis pipelines (python) What is it like ...

vocabulary scene understanding, or scene graphs. Proficiency in Python and Deep Learning libraries such as PyTorch. GPU or graphics programming experience, such as custom CUDA kernels, shaders, or differentiable rendering. A track record of contributing to widely used open-source research codebases. Nice to Have Proficiency in C++. Compensation ...

time alerts. Experience with transformer‐based and multimodal architectures, including vision‐language models (VLM), vision‐language‐action models (VLA), or equivalent. Proficiency in C++, CUDA, distributed training, or performance optimization for production machine learning systems. This is a full‐time role based in our office in London. At Wayve ...

with tight constraints (latency, memory, bandwidth, power/thermal, or cost). Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL, MLIR, ONNX) and confidence learning adjacent frameworks quickly. Comfort operating at multiple levels of abstraction — from high-level model behaviour ...

with tight constraints (latency, memory, bandwidth, power/thermal, or cost). 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 ...

deployments, monitoring and alerting stacks, and hardware acceptance and regression testing. Deep familiarity with the NVIDIA technology stack, including HGX platforms, NVLink/NVSwitch, CUDA-level debugging, and NCCL performance tuning. Strong leadership skills with the ability to set technical direction, solve complex problems, and guide engineering teams. Excellent ...

into existing AI and HPC infrastructure. Its current PT-2 system, a rack-mounted quantum computer, connects directly to GPU clusters via NVIDIA’s CUDA-Q platform, enabling accelerated AI workloads with significantly lower energy consumption than traditional silicon-based systems. Backed by a strong portfolio of patent families ...

PyTorch, Triton, and advanced scheduling tools like Kubernetes or Ray. Ideal candidates bring 3+ years in AI infrastructure, strong Python skills, and hands-on CUDA/C++ experience, with a degree in CS/EE/Applied Math. #J-18808-Ljbffr ...

production. The role involves optimizing training pipelines on HPC clusters, integrating ML models where latency matters, and working with C/C++, Python, CUDA, and other low-level GPU languages in a #J-18808-Ljbffr ...

architectures Optional Bonus Research engagement: advanced degree with research output, top-tier publications (NeurIPS, ICML, MLSys, OSDI), or open-source contributions GPU kernel work - CUDA, Triton, or similar Experience with quantisation, speculative decoding, disaggregated inference, or KV-cache compression Shortlisted candidates will be contacted within 48 hours. #J ...

this role, candidates must have been resident in the UK for at least five years. Desirable Experience MATLAB/Simulink OpenGL or Vulkan CUDA or OpenCL FPGA or HDL exposure Video processing or machine learning Background in defence, aerospace, automotive, or another high-reliability industry #J-18808-Ljbffr ...

these — as long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from ...

into existing AI and HPC infrastructure. Its current PT-2 system, a rack-mounted quantum computer, connects directly to GPU clusters via NVIDIA’s CUDA-Q platform, enabling accelerated AI workloads with significantly lower energy consumption than traditional silicon-based systems. Backed by a strong portfolio of patent families ...