19 of 19 Remote CUDA Jobs in England

Strong mathematical and analytical problem-solving skills. Desirable Skills: Experience with C# .NET, WinForms, WPF, or the Qt/QML framework, or HTML5. Experience in GPU programming (e.g., OpenCL, CUDA). Knowledge of AI and Machine Learning techniques. Expertise in graphics development (2D/3D) using technologies such as OpenGL, OpenGL Shaders, VTK, OSG, or Vulkan. Why apply for More ❯

Qt, QML); 3D graphics toolkits (OpenGL, Vulkan or shaders); CI experience (CMake, JIRA, Git, Jenkins); GIS development tools (GDAL API, MapBox API); multithreading/parallel computing (GPU programming or CUDA); MATLAB/Python scripting for mathematical/geology problems would be advantageous. Due to specific requirements, applicants without the relevant project experiences will not be considered (similarly exposure to More ❯

Qt, QML); 3D graphics toolkits (OpenGL, Vulkan or shaders); CI experience (CMake, JIRA, Git, Jenkins); GIS development tools (GDAL API, MapBox API); multithreading/parallel computing (GPU programming or CUDA); MATLAB/Python scripting for mathematical/geology problems would be advantageous. Due to specific requirements, applicants without the relevant project experiences will not be considered (similarly exposure to More ❯

Video Codec Experience: Familiarity with standard video codecs (e.g., H.264, H.265, AV1) and their integration in media pipelines. GPU Programming: Hands-on experience with GPU programming technologies, such as CUDA or OpenCL, to optimise performance for high-computation tasks. Scripting Knowledge: Proficiency in at least one scripting language like Python for automation and tool integration. Mentoring Junior Engineers: Experience More ❯

including advanced OpenCV, Boost, Standard library, and Jsoncpp for efficient data processing and manipulation. Implement machine learning models for object detection, particularly using YOLOv5, and optimize performance using Nvidia CUDA hardware acceleration. Develop, test, and deploy cloud-based applications and simulations, using Azure DevOps, Docker, and cloud-based agents for continuous integration and deployment. Write and maintain unit tests More ❯

Good oral and written English skills "Nice To Have" Skills and Experience : Experience with ML software frameworks (e.g. PyTorch) Familiarity with ML hardware accelerators (e.g. NPUs, TPUs, GPUs with CUDA support) Knowledge of optimising and profiling software Experience with assembly programming Software development and integration on Linux, Android, or similar systems Knowledge of scripting languages, including Python In Return More ❯

. Exposure to provisioning and automation tools (e.g., Ansible, PXE, Terraform). Experience with monitoring tools such as Prometheus, Grafana, and DCGM. Understanding of GPU/accelerator toolchains like CUDA or ROCm. A proactive, customer-first mindset with strong communication skills. Ability to work effectively in both individual and team settings. Comfort operating in fast-paced, ambiguous, high-growth More ❯

other high-performance media/signal-processing experience (broadcast, streaming, game engines, AR/VR). SIMD/vectorization (SSE/AVX/NEON) and/or GPU compute (CUDA, Metal, Vulkan, DirectCompute) for acceleration. Cross-platform build & packaging (CMake, cross-compilation toolchains, SDK distribution). CI/CD & DevOps practices (GitHub Actions, GitLab CI, Jenkins) and automated quality More ❯

above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience Desirable Strong software engineering experience in Python and other relevant languages (e.g. C++ and CUDA) Direct experience working in at least one of computer vision, robotics, simulation, graphics, or large language models. MS, or above in Machine Learning, Computer Science, Engineering, or a related More ❯

or create insights, that's a plus. Deeper systems knowledge. Extraexperience with any of the following would be an asset: developing GPU kernels and/or ML compilers (e.g. CUDA, OpenCL, TensorRT Plugins, MLIR, TVM, etc); optimizing systems to meet strict utilization and latency requirements with tools such as Nvidia NSight; and/or you've worked with embedded More ❯

or create insights, that's a plus. Deeper systems knowledge. Extraexperience with any of the following would be an asset: developing GPU kernels and/or ML compilers (e.g. CUDA, OpenCL, TensorRT Plugins, MLIR, TVM, etc); optimizing systems to meet strict utilization and latency requirements with tools such as Nvidia NSight; and/or you've worked with embedded More ❯

novel solutions. About you: C++ is your strongest language Ideally experience in Video or Audio Processing Experience writing performance-critical software Exposure to GPU technology (Vulkan API, OpenGL, OpenCL, CUDA etc.,) Relevant degree Full details are available. Please don't hesitate to get in touch with maxATplatform-recruitment.com to learn more. More ❯

novel solutions. About you: C++ is your strongest language Ideally experience in Video or Audio Processing Experience writing performance-critical software Exposure to GPU technology (Vulkan API, OpenGL, OpenCL, CUDA etc.,) Relevant degree Full details are available. Please don't hesitate to get in touch with (email address removed). com to learn more. More ❯

other high-performance media/signal-processing experience (broadcast, streaming, game engines, AR/VR). SIMD/vectorization (SSE/AVX/NEON) and/or GPU compute (CUDA, Metal, Vulkan, DirectCompute) for acceleration. Cross-platform build & packaging (CMake, cross-compilation toolchains, SDK distribution). Please get in touch with to hear more about this incredible position More ❯

Desirable skills: Experience in solving non-linear least square problems Experience with Computer Vision Experience in UI development e.g. ImGui Understanding of multithreading techniques Experience with GPU programming e.g. CUDA Experience with a messaging framework, e.g. NATS, RabbitMQ Experience working in and configuring cloud environments (e.g. AWS, Azure, GCP) Experience working with software containers (Docker, Podman) and container orchestration More ❯

Desirable skills: Experience in solving non-linear least square problems Experience with Computer Vision Experience in UI development e.g. ImGui Understanding of multithreading techniques Experience with GPU programming e.g. CUDA Experience with a messaging framework, e.g. NATS, RabbitMQ Experience working in and configuring cloud environments (e.g. AWS, Azure, GCP) Experience working with software containers (Docker, Podman) and container orchestration More ❯

ML codebases Hands-on with PyTorch, JAX or 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 Food: Daily lunch More ❯

of shipping deep learning systems to production. Expert in deep learning (esp. sequential models, control, planning, or perception). Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices. Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components. More ❯

optimise state-of-the-art algorithms and architectures, ensuring compute efficiency and performance. Low-Level Mastery: Write high-quality Python, C/C++, XLA, Pallas, Triton, and/or CUDA code to achieve performance breakthroughs. Required Skills Understanding of Linux systems, performance analysis tools, and hardware optimisation techniques Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.) Expertise … with machine learning frameworks (JAX, Tensorflow, PyTorch etc.) Passion for profiling, identifying bottlenecks, and delivering efficient solutions. Highly Desirable Track record of successfully scaling ML models. Experience writing custom CUDA kernels or XLA operations. Understanding of GPU/TPU architectures and their implications for efficient ML systems. Fundamentals of modern Deep Learning Actively following ML trends and a desire … to push boundaries. Example Projects: Profile algorithm traces, identifying opportunities for custom XLA operations and CUDA kernel development. Implement and apply SOTA architectures (MAMBA, Griffin, Hyena) to research and applied projects. Adapt algorithms for large-scale distributed architectures across HPC clusters. Employ memory-efficient techniques within models for increased parameter counts and longer context lengths. What We Offer: Real More ❯