1 to 25 of 39 CUDA Jobs in London

communication skills. Desirable experience Vision Transformer architectures. Object detection, tracking, segmentation or pose estimation. Multi-object localisation or multi-modal perception systems. GPU optimisation, CUDA, inference acceleration or edge AI. Real-time computer vision systems. Docker, Kubernetes, Kubeflow or MLOps pipelines. Aerial, satellite or ISR imagery. Synthetic data generation ...

building things properly the first time, even under early‐stage constraints. Nice to Have Experience with GPU cluster management and ML training workloads (NVIDIA, CUDA, distributed training). Familiarity with MLOps tooling: Experiment tracking (MLflow, Weights & Biases). Workflow orchestration (Airflow, Prefect, Argo). Data versioning (DVC). Background ...

ingestion, transformation, validation, versioning, republish — ideally including real‐world sources with rate limits, auth, or undocumented APIs. Hands‐on GPU compute and performance debugging (CUDA/NCCL, GPU utilization, networking bottlenecks, profiling). Working knowledge of cloud environments (AWS, GCP, or Azure), including object storage, IAM, and cost awareness. ...

operators and custom controllers for ML workloads Advanced Slurm administration including multi-cluster federation and advanced scheduling policies Familiarity with GPU cluster management and CUDA optimization Experience with other ML frameworks like TensorFlow or distributed training libraries Background in HPC environments, parallel computing, and high-performance networking Knowledge ...

into reliable software. Experience developing maintainable code using version control, testing and CI/CD. Strong analytical, problem-solving and communication skills. Desirable experience CUDA and GPU programming. Python and PyTorch. CNNs, Transformers or broader deep learning architectures. Synthetic training imagery and simulation environments. ISR imagery or defence-related ...

lifecycle of models in a multi‐tenant, high‐availability system. Familiarity with building ML inference services, model serialization (e.g., ONNX), and GPU programming (CUDA). You've built or worked on custom storage or job‐queueing systems before and have the scars to prove it. Maybe ...

independently drive research projects from idea generation through experimentation and publication. Nice to Have Experience with classical reconstruction tooling (COLMAP etc). C++ or CUDA, and a feel for performance and on-device constraints. #J-18808-Ljbffr ...

research goals with practical engineering constraints Strong problem-solving skills, results orientation, and excellent collaborative communication Reliable and predictable availability Bonus Points Expertise in: CUDA kernel development, Triton/Pallas/CuTe DSLs, PyTorch/JAX internals, XLA optimization, or hardware acceleration (FPGA/ASIC) Knowledge of reinforcement learning ...

fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton. Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling. Practical familiarity with ...

independently drive research projects from idea generation through experimentation and publication. Nice to Have Experience with classical reconstruction tooling (COLMAP etc). C++ or CUDA, and a feel for performance and on-device constraints. Compensation & Benefits £96,300 - £107,000 + bonus/equity/benefits Location & Work Model ...

training frameworks, GPU/accelerator optimization, data pipelines, experiment tracking, and making research reproducible and reliable. You have experience down to the level of CUDA kernels or XLA. You have contributed to open source projects like PyTorch, JAX, MLX or similar. You care about research outcomes as much ...

TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline chops. Strong software‐design instincts: testing, code review, CI/CD. Self‐starter, low‐ego, collaborative. Benefits France 💰 Competitive cash salary and equity ...

performance of XTX's training and inference platforms. The remit is wide, and you should expect to be challenged. We are not just writing CUDA code. Amongst other things, you will be working on a sophisticated optimising compiler for a variety of accelerated computing platforms. You should be proficient ...

strong focus on memory management, multi-threading, and low-level performance optimizations Experience with GPU architectures (e.g., NVIDIA, AMD) and programming frameworks like CUDA, OpenCL, and TensorFlow Understanding of machine learning algorithms, including model training and inference, and how to optimize these for GPU-based computation Strong knowledge ...

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. Benefits Opportunity to work at one of the world's leading algorithmic trading firms Engaging projects offering accelerated responsibilities and ownership ...

PyTorch ecosystem Experience with inference optimisation techniques, including quantisation, speculative decoding and model parallelism across modern GPU architectures Strong software engineering skills, including Python, CUDA and building reliable systems for machine learning workloads Strong communication skills, with the ability to collaborate across research, infrastructure and engineering teams Why join ...

systems, including vector database management and semantic search optimization. Preferred Qualifications Experience in the insurance or financial services sector. Deep knowledge of GPU architecture , CUDA, and hardware-level performance optimization. Familiarity with Document Intelligence frameworks (OCR, layout analysis, and multimodal extraction). MUST be fluent in Mandarin OR Cantonese ...

exceptional academic record. Experience with HPC, supercomputing or large-scale distributed systems. Research experience involving computational workloads. Experience with parallel programming (MPI, OpenMP, CUDA). Knowledge of scheduling systems such as Slurm, PBS or LSF. Contributions to technical projects, open source or research communities. Experience working with advanced computing … Scale Computing, Scientific Computing, Numerical Computing, Computational Science, Computational Engineering, Performance Engineering, Performance Optimisation, Benchmarking, Profiling, Low Level Programming, C++, C, Python, Fortran, Rust, CUDA, GPU Computing, GPU Acceleration, Parallel Programming, MPI, OpenMP, Multithreading, Concurrency, Algorithms, Data Structures, Systems Design, Kernel Development, Networking, Storage Systems, Distributed Storage, Automation, Infrastructure ...

SLURM, PBS, or equivalent), MPI/NCCL tuning, and distributed training frameworks such as PyTorch, JAX, or DeepSpeed. Deep understanding of GPU software environments: CUDA, cuDNN, NCCL, driver stacks, and the tooling required to run large-scale AI training and inference workloads reliably in production. Hands-on experience optimising ...

Experience with CPU and/or GPU concurrent programming English language fluency (both written and verbal) Preferred Qualifications Experience with GPU APIs (preferably Metal, CUDA, Vulkan or DX12) Experience with rendering and/or parallel compute algorithms Familiarity of one or more GPU architectures and how to optimize rendering ...

must, or you have previous experience training models (strong math skills are still required). Strong PyTorch experience. Strong ability to code in Rust, CUDA, or C (with a preference for Rust). Solid understanding of Transformers (not the movies). A product mindset. you’ll be building things ...

plus; a strong background in mathematics is required. Alternatively, experience training models with strong math skills. Strong coding ability in Rust (preferred), CUDA, or C. Solid understanding of transformer architectures. A product mindset; you’ll build production‐ready products. Hybrid Remote with the London Office. What ...

apply advanced techniques, optimize training pipelines on HPC clusters, and integrate ML models into latency-sensitive production environments, using C/C++, Python, and CUDA across large-scale systems. #J-18808-Ljbffr ...

systems for quantitative finance. You will optimize training pipelines, deploy models to low-latency production environments, and work across C/C++, Python, CUDA, and related GPU technologies. Join a fast-paced, collaborative team focused on impactful projects that push the boundaries of AI research and its applications ...

front and centre. Strong candidates may also have Experience with a systems programming language like Rust or C++. Experience with writing and profiling CUDA kernels. A track record of building reliable research tools. Why this is interesting You’ll shape the core technical foundation of a frontier ...