23 of 23 CUDA Jobs in London

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

optimize the end-to-end ML stack: data pipelines, training loops, inference serving, and deployment. Design and implement GPU-accelerated components, including custom CUDA kernels where off-the-shelf libraries are not enough. Work closely with the founders to translate product requirements into concrete optimization goals and technical roadmaps. ...

will focus on throughput, accelerator utilization, and robust tooling, collaborating with researchers and engineers across teams. The role emphasizes low-level kernel work (CUDA/Triton), distributed training strategies, and cutting-edge ML infrastructure to drive efficient language understanding and generation. #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 ...

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 ...

such as oil and gas, automotive/aerospace, financial services, or pharmaceuticals. Proficient in one or more of the following programming languages: C++, Python, Cuda, or Bash. Experience in architecting an HPC platform with scheduling middleware (e.g., Slurm, Torque, Symphony or GridServer) and in deployment, tuning and management … programming models for both loosely and tightly coupled applications, including proficiency with MPI (OpenMPI, MPICH), OpenMP, and hybrid parallelization strategies, and GPU programming using CUDA, OpenACC, or similar technologies, with demonstrated ability to optimize applications for GPU architectures. Significant experience in infrastructure architecture and networking. Experience with infrastructure ...

frameworks such as PyTorch or JAX Are proficient in Python, including concurrency, asynchronous programming, multiprocessing, and performance optimization Can debug distributed GPU workloads across CUDA runtime, container runtime, driver versions, NCCL or equivalent communication layers, networking, storage, scheduling, and checkpointing Have experience with profiling tools across the stack … Experience with GPU clusters on Kubernetes, Slurm, Ray, custom schedulers, or cloud GPU orchestration NCCL, UCX, NVSHMEM, RDMA, InfiniBand, RoCE, or EFA Rust, C++, CUDA, Go, or systems‐level performance work Why White Circle You will be able to propose and run your own experiments and research ideas ...

will collaborate closely with researchers to co‐design and improve our models and shape the research agenda. Qualifications Strong engineering skills, especially in CUDA/Triton/Pallas/CuTe DSL kernel development, lower‐level PyTorch/JAX/XLA development, CUDA Graphs, FPGA/ASIC experience. ...

demand, Fuse is expanding into high-performance compute infrastructure that sits at the intersection of energy and AI. We're building the GPU/CUDA performance layer and the inference serving layer at the same time, from scratch -- and we're looking for the founding engineer … Founding AI Inference Engineer to define and build how Fuse serves AI inference workloads at scale, reporting directly to the CTO. Where our CUDA and GPU engineering hires own kernel-level and hardware performance, this role owns the layer above it: how models actually get served, scaled, and delivered ...