Future Tech Jobs
Future Tech Jobs
Design and deploy scalable AI and HPC GPU infrastructure in large-scale datacentres, focusing on power, cooling, and MEP integration. Collaborate with cloud partners to solve technical challenges in datacentre design and support real-world deployment of NVIDIA technologies. Provide expert guidance on infrastructure optimisation and contribute to product strategy through customer feedback.
Develop and optimize compilers for AI inference workloads on next-generation NVIDIA GPUs, focusing on kernel generation, computational graph optimizations, and hardware-software co-design. Collaborate with cross-functional teams to advance AI performance and scale across datacenters. Work at the forefront of compiler innovation for deep learning and AI architectures.
Work on AI and ML systems for a cloud platform that transforms audio and video into structured data. Engage in prompt engineering, retrieval systems, computer vision, and backend development within a small, agile R&D team. The role offers broad technical exposure and close collaboration with experienced engineers.
This role involves defining and evolving enterprise architecture strategies with a focus on AI, cloud-native systems, and distributed architectures. The architect will design scalable AI workloads, lead technical direction across cloud, data, and infrastructure domains, and translate complex technical concepts into strategic recommendations for senior stakeholders. Key responsibilities include assessing emerging technologies, shaping investment decisions, and establishing reusable enterprise design patterns in environments leveraging Azure, GCP, or AWS.
This PhD studentship focuses on developing AI-enhanced flexible antenna systems for next-generation wireless networks, specifically targeting 6G technologies. The research will explore AI-driven methods for channel estimation, beamforming, and real-time network optimisation to improve system resilience, energy efficiency, and coverage in dynamic environments. The candidate will work within a research group at The University of Manchester, contributing to cutting-edge advancements in wireless communication systems.
This PhD studentship focuses on developing AI-enhanced flexible antenna systems for next-generation wireless networks, targeting 6G applications. The research will explore AI-driven methods for channel estimation, beamforming, and real-time network optimisation to improve reliability, energy efficiency, and resilience in dynamic environments. The candidate will work within a research group at The University of Manchester, combining antenna engineering and machine learning techniques.
Design and develop digital solutions using Microsoft Power Platform, including Power Apps and Power Automate, within an agile environment. Collaborate with business stakeholders and IT teams to deliver low-code applications, with opportunities to work on AI-enabled features. Focus on creating custom connectors and automating workflows across business functions.
Lead the end-to-end development and deployment of production-grade generative AI solutions across client-facing digital products. Design and optimise RAG systems, semantic search, and large language model applications while guiding engineering teams and shaping AI strategy in collaboration with senior leadership. Focus on scaling AI-driven features and improving business efficiency across a high-growth technology environment.
This role involves designing and building AI-powered products and platforms using Golang within Citi's high-growth AI Product & Platform team. You'll develop scalable backend services and cloud-native microservices, collaborate with AI specialists, and contribute to developer tools and frameworks. The position emphasizes innovation in distributed systems, generative AI, and modern engineering practices in a start-up-like environment within a global financial institution.
Discover your future at CitiWorking at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your...
Design and lead the development of production-grade AI systems that analyze live sports video and data to generate real-time insights and enhance fan experiences. Work closely with engineering and data science teams to architect scalable, low-latency machine learning systems, maintaining hands-on involvement in solving complex technical challenges. Play a key technical leadership role without direct reports, shaping system design and raising engineering standards across the platform.
This role involves leading the design of AI-native product surfaces for Synthesia, focusing on creating engaging and natural conversational experiences, AI-driven workflows, and high-quality localisation processes. You will set design direction, influence product roadmaps, and work closely with Product and Engineering to define and achieve high standards in AI-native interactions.
Develop and apply deep learning models for land cover classification and change detection using multi-source aerial and satellite imagery. Work within an interdisciplinary team on the Landscape Observatory project, leveraging HPC and GPU infrastructure to advance AI-powered remote sensing for environmental monitoring. Contribute to high-impact research, publish in scientific journals, and present at international conferences.
Lead the design and implementation of AI-driven risk decisioning systems, focusing on fraud detection, credit risk, and financial crime. Develop scalable, cloud-native platforms using event-driven architectures and real-time processing, while mentoring engineering teams and shaping technical strategy. Work within a regulated environment to translate compliance and risk requirements into robust, production-grade solutions.
This role involves conducting research and delivering teaching in digital transformation and AI for business within a Russell Group university. The postholder will contribute to programs such as the MSc in AI for Business and BSc in Business and Intelligent Technologies, with opportunities to engage in research centres like CDR and TOSCA. Teaching spans topics including digital innovation, intelligent technologies, and explainable AI.
