17 of 17 CUDA Jobs in London

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. ...

science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. Experience configuring and maintaining cloud ...

professional industry setting, where you have been instrumental in: building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch/CUDA, ideally with exposure to JAX, NumPy/SciPy), especially including deep learning applications; developing models for bespoke problem settings that involve high‐dimensional data ...

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 ...

development, ideally in legged robotics; Knowledge of locomotion, whole-body control, or state estimation systems; Experience with distributed heterogeneous compute architectures, including GPGPU and CUDA; Strong understanding of pub/sub communication systems, telemetry, logging, and visualisation pipelines; Experience with task orchestration, behaviour trees, state machines, mission planning ...

automation and orchestration systems for these platforms Proficiency in a low-level language such as C, C++, or Rust and in GPU frameworks like CUDA Competence in front-end web design to allow easy interfacing with large datasets Our Culture Follow the science. We prioritise rigorous scientific inquiry, relying ...

with research teams to accelerate large-scale model training 🔧 What They’re Looking For Deep GPU infrastructure/distributed systems experience Strong knowledge of CUDA, NCCL, PyTorch, DeepSpeed, JAX, Megatron-LM, vLLM, etc. Experience operating large-scale GPU clusters (1,000+ GPUs) Kubernetes, Slurm, or similar orchestration expertise BONUS ...

science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. At a personal level ...

MLOps architecture. Willingness to learn new parts of the ML tech stack – Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and model serving frameworks. Fluency in life sciences or drug discovery is a plus. Working Location & Compensation: This is an office‐based, hybrid position ...

excited by applying those skills to one of the most interesting data domains in AI. Areas of interest include: PyTorch/JAX internals CUDA, XLA or Triton optimisation Distributed training systems GPU cluster performance tuning Large-scale experiment management Training reliability and reproducibility Kubernetes and orchestration tooling Infrastructure supporting ...

3+ years in computer vision or AI engineering Experience training and deploying CV models Strong mathematical and analytical skills Nice to Have Edge deployment CUDA Multi-camera systems ...

codec, VAD, enhancement, or similar) Familiarity with Arabic linguistic structure, diacritization tools, and NLP preprocessing for Arabic Experience with inference optimization — quantization, speculative decoding, CUDA kernels, or serving frameworks (vLLM, TensorRT) Publications or open-source contributions in speech or audio What We Offer Work at the frontier of Arabic ...

lead candidates: Hire and mentor a small team of exceptional engineers and researchers Qualifications You've written and shipped high-performance or SOTA CUDA kernels Deep understanding of mixed precision, quantisation (INT4, INT8, FP8, MXFP4, block-scaled formats), kernel fusion, distributed computing strategies (TP, PP, CP) You've made ...

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 ...

level optimisation Develop pricing models using numerical techniques such as Monte Carlo methods and partial differential equation (PDE) solvers Work with technologies including C++, CUDA, Python, and adjoint algorithmic differentiation (AAD) Contribute to the technical direction of the group, mentor junior team members, and collaborate closely with quant teams … experience in a high‐performance computing or numerical software role (experience outside of finance will be considered) Strong programming skills in C++; experience with CUDA and Python preferred Excellent background in computational mathematics, numerical analysis, or a related quantitative discipline Demonstrated ability to design, implement, and optimise complex mathematical ...

about efficient large-scale training, low-latency inference in real-time systems and high-throughput inference in research. Part of this is improving straightforward CUDA, but the interesting part needs a whole-systems approach, including storage systems, networking and host- and GPU-level considerations. Zooming in, we also want … end. Low-level GPU knowledge of PTX, SASS, warps, cooperative groups, Tensor Cores and the memory hierarchy. Debugging and optimisation experience using tools like CUDA GDB, NSight Systems, NSight Compute-sight-systems and nsight-compute. Library knowledge of Triton, CUTLASS, CUB, Thrust, cuDNN and cuBLAS. Intuition about the latency ...

Quant Blueprint LLC is seeking an engineer proficient in low-level systems programming and optimization to enhance our machine learning team. This role centers on optimizing model performance, both for training and real-time inference. ...