14 of 14 CUDA Jobs in the City of London

approach to AI implementation. Effective communication and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯

Experience: Proficiency in C++ with a 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 of parallel computing, vectorization, and More ❯

at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional teams and present complex ideas to both technical and non More ❯

of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical audiences. Knowledge of quantitative finance More ❯

e.g., Unreal Engine, Unity, custom 3D engines). Proven track record of publications at top-tier conferences (e.g., NeurIPS, CVPR, ICML, ICLR, SIGGRAPH, ECCV). Experience with GPU programming (CUDA) and model optimization for real-time inference (e.g., quantization, pruning, ONNX, TensorRT, custom CUDA kernels). Background in scalable algorithm design for real-time or interactive applications. Experience More ❯

across diverse vendor platforms. Working with low-level system and memory management techniques to minimize latency and improve real-time inference performance. Utilizing and implementing GPU programming APIs (e.g., CUDA, OpenCL) to ensure high efficiency and compatibility across GPUs. Profiling and debugging system performance using tools like NVIDIA Nsight, Intel VTune, and vendor-specific profilers, identifying bottlenecks and implementing … autonomous systems. Essential Requirements: 3+ years of experience in C++ programming, with a strong grasp of modern C++ standards. Proven experience in GPU programming and optimization, with proficiency in CUDA, OpenCL, or other GPU programming frameworks. Strong knowledge of parallel computing concepts, including data locality, memory access patterns, and synchronization. Proficiency with performance profiling tools and techniques for identifying More ❯

Social network you want to login/join with: Senior CFD Software Engineer, london (city of london) col-narrow-left Client: IC Resources Location: london (city of london), United Kingdom Job Category: Other - EU work permit required: Yes col-narrow More ❯

Senior CFD Software Engineer London I'm currently supporting a Fortune 100 organisation and a global leader. In this role, you will design and enhance solver features for both CPU and GPU, as well as develop pre- and post-processing More ❯

Industrial experience in deploying SLAM solutions. Proficiency in C++. Desirable experience: PhD in computer vision or robotics. Experience with machine learning techniques for geometric & semantic estimation. GPU programming skills (CUDA, OpenCL, Vulkan, Metal). Experience with embedded software development. If this role is of any interest please apply directly on LinkedIn or send a copy of your CV to More ❯

to-end AI solutions at scale. Essential Requirements: Proven experience as an Engineering Manager delivering complex engineering projects. Expertise in developing GPU kernels and/or ML compilers (e.g., CUDA, OpenCL, TensorRT, MLIR, TVM). Experience optimizing systems to meet strict utilization and latency requirements. Excellent interpersonal and communication skills. Desirable: Experience with C++ and ML frameworks such as More ❯

and platform teams Troubleshoot and optimise GPU usage across a variety of hardware and OS environments What they’re looking for Solid experience with low-level GPU programming using CUDA, Vulkan, OpenCL, Metal or similar Strong C or C++ skills and a background in systems or performance engineering Deep understanding of how modern GPUs work, including memory and compute More ❯

/CD pipelines using GitHub Actions . Experience with analytics platforms like Google Analytics and business intelligence tools like Tableau or Power BI. Knowledge of GPU-accelerated computing with CUDA is highly desirable. Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity startup environment. 🌟 Cultural Fit - Intensity Required Ultralytics is a high-performance More ❯

of model architectures like transformers and CNNs. Hands-on experience with model optimization (i.e. quantization, pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO. Proficiency with CUDA programming and optimizing code for GPU acceleration. Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker. Excellent problem-solving skills and the More ❯

using Docker and orchestrating them with Kubernetes for scalable model serving. Optimizing the performance of our Ultralytics YOLO11 models for various deployment targets, from high-performance cloud GPUs with CUDA to edge devices using frameworks like TensorRT and OpenVINO. Implementing robust systems for model monitoring and maintenance to track performance and detect data drift. Collaborating closely with our AI … experience with at least one major cloud provider ( GCP , Azure, AWS). Experience with Infrastructure as Code (IaC) tools such as Terraform or Ansible. Familiarity with GPU acceleration using CUDA and model optimization for inference. Knowledge of MLOps tools for experiment tracking, and model serving such as MLflow, Kubeflow, or Weights & Biases. Excellent problem-solving skills and the ability More ❯