5 of 5 CUDA Jobs in East 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 ❯

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 ❯

Experience deploying SLAM in industrial or embedded environments Proficient in modern C++ development Preferred Familiarity with machine learning for semantic/geometric inference. Experience in GPU computing, e.g. Vulkan, CUDA, OpenCL or Metal Exposure to embedded systems development. Feel free to also refer someone you may know who could be good for the role. If they are successfully placed … we offer a great referral scheme! Key words – Visual-inertial Odometry/SLAM/Computer Vision/Robotics/CUDA/Vulkan/OpenCL/Metal/Sensor Fusion/Embedded Systems/Semantic Inference/Geometric Inference/C++/Spatial AI By applying to this role, you understand that we may collect your personal data & store & process More ❯

global trading operations. Engineer core platform components: memory allocators, kernel bypass, custom RPC, and distributed compute frameworks. Optimise performance at the hardware/software boundary, including GPU acceleration and CUDA-based compute. Work on Linux kernel internals, networking stacks, and system-level debugging. Technical Requirements: 3+ years of experience in C++ (C++17/20) with strong knowledge of memory … management, concurrency, and performance tuning. Experience with GPU programming (CUDA), SIMD, and kernel-level development. Deep understanding of data structures, lock-free algorithms, and low-latency systems. Familiarity with Linux internals, system calls, and performance profiling tools. Background in platform engineering, distributed systems, or high-performance computing. Preferred Background: Participation in competitive programming contests (IOI, ICPC, Codeforces, etc.). More ❯

as-code mindset Hands-on experience resolving GPU workload issues across compute clusters and supporting technologies Familiarity with performance tooling and debugging in live production environments Practical experience with CUDA or systems-level programming in C/C++ Experience with config management frameworks like Salt, Ansible, or Puppet (Preferred) Experience with GPU communication and interconnect technologies (e.g. collective communication More ❯