Description About KX Our mission is to accelerate data and AI-driven innovation with high-performance analytics solutions, enabling our customers to transform into AI-first enterprises. KX is trusted by the world's top investment banks & hedge funds, aerospace and defence, life and health sciences, semiconductor, telecommunications, and advanced manufacturing companies. Time series and vector data analytics and management are at the heart of our products, independently benchmarked as the fastest on the market. They help our customers process data at unmatched speed and scale and empower LOB leaders, developers, data scientists, and data engineers to build high-performance data-driven applications and turbocharge their favourite analytics tools in the cloud, on-premise, or at the edge. KX technology enables the discovery of richer, actionable insights for faster, better-informed decision-making, which drives competitive advantage and transformative growth for our customers. KX operates across North America, Europe, and Asia Pacific. Role Overview: As a CUDA Engineer, the successful candidate will play a pivotal role in designing, developing, and optimizing GPU-accelerated solutions to address complex computational challenges. The ideal candidate will be highly skilled in CUDA programming and GPU optimization techniques, with a strong understanding of parallel computing principles. A key focus will be low-level optimizations leveraging the latest hardware advancements, including efficient utilization of Tensor Memory Accelerator (TMA) features, warp-level programming techniques, asynchronous execution models, and advanced memory hierarchies for modern GPUs. The successful candidate will collaborate closely with cross-functional teams to deliver efficient, scalable, and innovative solutions tailored to our products and customers' needs. Key Responsibilities: Design and develop high-performance GPU-accelerated algorithms using CUDA. Optimize existing CUDA-based applications to maximize efficiency and scalability on modern GPU architectures. Collaborate with software engineers, data scientists, and product managers to integrate GPU-accelerated solutions into broader applications. Analyze performance bottlenecks and develop innovative strategies for improving performance. Stay up-to-date with the latest GPU technologies, tools, and techniques to ensure optimal performance and application design. Debug, troubleshoot, and maintain GPU-accelerated software across different environments. Work with libraries such as cuBLAS, cuDNN, and other NVIDIA toolkits to implement and optimize solutions. Provide technical guidance and mentorship to team members on CUDA programming and GPU optimization. Requirements: 6 years of experience in CUDA development for GPU-based systems. Strong knowledge of parallel computing concepts and GPU architecture. Proficiency in C/C++ programming with experience in GPU acceleration frameworks. Experience working with NVIDIA GPU tools such as Nsight Systems and Nsight Compute. Familiarity with machine learning and deep learning frameworks such as TensorFlow or PyTorch is a plus. Strong problem-solving skills and the ability to debug and optimize GPU-accelerated software. Excellent interpersonal and communication skills for collaboration across teams. Bachelor’s degree in Computer Science, Software Engineering, or a related field (Master’s preferred). Location & Workplace Type: This position takes on a hybrid working model, based in London, Belfast, Newry, Dublin or Toronto. Why Choose KX? Data Driven: We lead with instinct and follow fact. Naturally Curious: We lean in, listen, and learn fast. All In: We take ownership, take on challenges, and give it our all. Benefits: Competitive Salary Individually tailored training and skills development Private healthcare package and Employee Assistance Programme Enhanced maternity and paternity package Wellness Days and Volunteer Days