Future Tech Jobs
Future Tech Jobs
Latest UK roles, updated daily.
We are looking to hire a senior CPU Compiler performance Engineer for an exciting and fun role at NVIDIA. We craft outstanding compilers that realise the potential of NVIDIA's CPUs designed for the world's largest AI and computing markets: https://www.nvidia.com/en-in/data-center/grace-cpu/....
We are looking to hire a senior CPU Compiler performance Engineer for an exciting and fun role at NVIDIA. We craft outstanding compilers that realise the potential of NVIDIA's CPUs designed for the world's largest AI and computing markets: https://www.nvidia.com/en-in/data-center/grace-cpu/....
We are looking for a Solution Architect for the Telecommunications Industry team with domain specific knowledge and experience in AI and telecom operation. At NVIDIA, our Solution Architects are drawn from best-in-class engineers, architect, developers, and scientists who enjoy working...
Senior Linux IAM EngineerEdinburgh or GlasgowRelaxed Hybrid and Flexible Working Environment£58,281- £68,621 per annum + 28.97% employer contributory pension and 38 days annual holidayIntroduction to the RoleHays' Cyber practice have partnered exclusively with Registers of Scotland (RoS) on the search...
This role involves building and supporting data products within a modern data platform, developing scalable data pipelines, and integrating diverse data sources with strong quality standards. The engineer will work in agile, multi-functional teams to support machine learning and generative AI infrastructure, while promoting best practices in data engineering and collaborating with data scientists and architects.
Darktrace is a global leader in AI for cybersecurity that keeps organizations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly 10,000 organizations from unknown threats using its proprietary AI....
Develop and scale physical foundation models by bridging research and engineering, transforming prototypes into robust, optimised AI-driven simulation systems. Work across scientific computing, distributed training, and cloud infrastructure to deliver high-impact solutions for real-world engineering problems in collaboration with research teams, customers, and partners.
This role involves developing AI-driven physical foundation models to solve complex engineering challenges in domains like aerospace, energy, and semiconductors. You'll translate physics-based problems into mathematical formulations and build scalable machine learning models—particularly using deep learning and probabilistic methods—for high-fidelity simulation. The position emphasizes research ownership, collaboration with engineers and customers, and publishing impactful work.
This role involves leading the development of a Windows kernel-mode security sensor that detects and prevents advanced threats at the endpoint level. You will design and implement core features across file systems, memory, networking, and process subsystems, ensuring high performance and cross-platform compatibility. Collaboration with distributed teams and ownership of features from concept to delivery are central to the role.
This role involves leading the development of a next-generation Windows kernel-mode security sensor for CrowdStrike’s endpoint protection platform. You'll design and build core features across file systems, memory, networking, and process subsystems, with a focus on performance, low-level OS integration, and cross-platform compatibility. The position requires deep expertise in C++ and Windows kernel development, and you'll collaborate with distributed teams to deliver high-impact security capabilities from concept to deployment.
This role involves leading the development of a Windows kernel-mode sensor for CrowdStrike’s endpoint security platform, focusing on next-generation anti-virus and threat detection. The engineer will design and implement core features that span file systems, memory, networking, and process management, ensuring high performance and cross-platform compatibility. Collaboration with distributed teams and ownership from concept through delivery are key aspects of the role.
Architect and develop scalable reinforcement learning post-training infrastructure that operates across GPUs, CPUs, and LPUs, from single-node experimentation to multi-thousand-node production systems. Work closely with AI researchers and infrastructure teams to optimize distributed training-inference-rollout loops, improve open-source RL frameworks, and integrate with distributed runtimes like Ray and Monarch. Focus on performance, fault tolerance, elastic scaling, and hardware-aware execution for next-generation AI workloads.
This role involves designing and building scalable reinforcement learning (RL) post-training infrastructure that supports the full lifecycle of training, inference, and rollout across heterogeneous hardware. The engineer will optimize distributed systems for performance, fault tolerance, and efficiency, working closely with AI researchers and infrastructure teams. Key responsibilities include improving open-source RL frameworks, enabling CPU- and GPU-accelerated workloads, and collaborating with hardware and compiler teams to support next-generation AI capabilities.
This role involves designing and building scalable reinforcement learning (RL) post-training infrastructure that supports the full lifecycle of training-inference-rollout loops across heterogeneous hardware. The engineer will contribute to open-source RL frameworks, optimize distributed systems for performance and resilience, and collaborate with research and hardware teams to advance AI capabilities. Work spans deep integration with PyTorch, Kubernetes, and high-performance computing environments to enable next-generation AI models.
This role involves working closely with top AAA game developers to optimize GPU performance and advance rendering technologies, particularly in path tracing and neural graphics. The engineer will develop and fine-tune AI models and rendering algorithms, collaborate with hardware and driver teams, and contribute to next-generation GPU architecture planning. They will also create technical demos, publish research, and present findings at industry conferences, driving innovation in AI and real-time graphics.
