System Engineer (Token Factory) in UK at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a System Engineer (Token Factory) based in United Kingdom.

Join a cutting-edge AI infrastructure team building the next generation of large-scale inference platforms. In this role, you will work on the core systems that make advanced AI models faster, more reliable, and easier to deploy at global scale. You will solve complex engineering challenges across GPU computing, hardware optimization, and low-level performance tuning while collaborating with experts in machine learning and backend systems. This is an opportunity to contribute directly to the future of AI infrastructure, working in a highly technical, international, and innovation-driven environment where engineering excellence and ownership are valued.

• Develop and optimize low-level kernels, runtime components, and system software responsible for high-performance AI inference workloads.
• Improve inference engine performance across GPU platforms by identifying bottlenecks and implementing advanced optimization techniques.
• Profile, debug, and resolve system-level and hardware-level performance issues across CPU and GPU environments.
• Integrate support for emerging GPU architectures and next-generation hardware platforms.
• Collaborate closely with machine learning and backend engineering teams to optimize end-to-end execution pipelines.
• Contribute to the continuous improvement of large-scale AI infrastructure through technical innovation, performance analysis, and system-level problem solving.

• Strong proficiency in C++ development or deep expertise in GPU programming focused on low-level, high-performance computing and memory management.
• Experience with GPU programming or systems-level software development, including operating system internals, kernel modules, device drivers, or comparable areas.
• Hands-on experience using profiling and debugging tools to analyze CPU and GPU performance issues and optimize code based on findings.
• Strong understanding of CPU/GPU architecture, memory hierarchy, and hardware performance considerations.
• Familiarity with GPU computing technologies such as CUDA, ROCm, CUTLASS, Triton, Pallas, Mosaic GPU, or similar frameworks is highly valued.
• Experience with machine learning inference runtimes such as TensorRT, TVM, or comparable technologies is a plus.
• Knowledge of Linux internals, compiler toolchains, drivers, and performance analysis tools such as perf, VTune, Nsight, or ROCm profiler is beneficial.
• Familiarity with modern inference engines and AI deployment frameworks is considered an advantage.
• Strong problem-solving skills, technical curiosity, and ability to collaborate effectively in a fast-paced engineering environment.

• Competitive compensation package.
• Fully remote working flexibility within Europe.
• Opportunity to work on impactful AI infrastructure projects at global scale.
• Strong opportunities for career development and continuous technical learning.
• High level of ownership and autonomy in a collaborative engineering culture.
• International environment with talented teams working on advanced AI technologies.
• Opportunity to contribute to the evolution of large-scale GPU computing and AI deployment platforms.