Lead business development and delivery for AI-driven simulation software within aerospace and defense, driving customer acquisition, shaping go-to-market strategy, and managing technical execution. Engage with senior engineering leaders, scope and deliver high-impact projects, and translate customer needs into product evolution. This hybrid role blends strategic sales with hands-on technical leadership and regular travel to customer sites.
This role involves building and running high-fidelity CFD simulations from geometry preparation to post-processing for moderately complex engineering cases. You'll work at the intersection of CAE and data science, supporting the development of AI-driven simulation models and contributing to automated workflows on cloud and HPC platforms. The position includes customer collaboration, model adaptation for deep learning surrogates, and occasional international travel to support on-site engagements.
The Maintenance Engineer supports the operation of a highly automated Customer Fulfillment Center by performing electrical and mechanical maintenance, diagnosing equipment faults, and carrying out planned and reactive repairs. The role involves working with advanced robotics systems, analyzing performance data, and contributing to continuous improvement initiatives. Candidates must be comfortable working nights, weekends, and at heights during shifts.
Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks. Design and execute performance studies to establish baselines, diagnose regressions, and quantify bottlenecks. Define evaluation methodologies and success metrics for AI workloads, using profiling and data analysis to drive optimization. Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
This role involves analyzing end-to-end performance of large-scale AI workloads across compute, networking, storage, and software stacks. The engineer will design performance studies, diagnose bottlenecks, and develop optimization strategies for AI systems running on NVIDIA's DGX Cloud infrastructure. Work includes close collaboration with deep learning engineers, platform teams, and architects to deliver measurable performance improvements at scale.
The role involves leading daily operations in an R&D facility focused on advanced underwater robotics, combining hands-on technical work with team coordination and safety leadership. The technician will build and test electro-mechanical systems, conduct data analysis, and support engineering design through practical experimentation. It’s a hands-on leadership role within a multidisciplinary engineering environment pushing the boundaries of subsea technology.
The role involves leading the adoption of Generative AI and machine learning in Treasury operations, focusing on liquidity forecasting, capital optimisation, and risk management. You'll design and deliver AI solutions, migrate systems to secure cloud environments, and promote responsible AI practices while mentoring engineers and shaping technical strategy. The position requires strong leadership in AI engineering, collaboration with stakeholders, and oversight of data governance and scalable architecture.
This role involves independently supporting and troubleshooting legal technology systems, evaluating emerging tools like generative AI, and providing training and documentation to improve system adoption. The analyst will monitor usage trends, liaise with vendors, and stay current with legal tech advancements. It's a senior position with responsibility for mentoring junior team members and driving technology improvements within a high-performing legal environment.
Lead the development and deployment of cutting-edge, production-grade machine learning systems for high-impact clients, particularly in the defence sector. Design scalable ML infrastructure, define best practices for ML deployment, and act as a technical advisor while mentoring junior engineers. Work in a cross-functional environment with strong emphasis on ethical, reliable AI and client collaboration.
Develop and deploy production-grade machine learning systems for high-impact clients, particularly in the defence sector. Work across the full ML lifecycle, from scalable architecture design to operationalisation, using cloud platforms and containerisation tools. Collaborate with cross-functional teams to deliver ethical, reliable AI solutions in real-world environments.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy AI systems that solve real-world business problems. The role involves hands-on coding, system integration, and technical leadership to guide AI solutions from prototype to production, with a focus on reliability, safety, and measurable impact. The position requires deep technical expertise and strong collaboration with both customer teams and internal OpenAI groups.
Lead high-value enterprise opportunities through the joint AWS and OpenAI co-sell motion, working closely with AWS field teams and OpenAI stakeholders to shape and close strategic AI and cloud transformation deals. Develop scalable playbooks and value propositions that align OpenAI’s capabilities with enterprise business priorities. Operate in a cross-functional, executive-facing role to drive commercial execution and pipeline growth.
Develop and evaluate AI-powered weather forecasting models tailored for African farming communities, focusing on sub-seasonal predictions. Design modular deep learning systems integrating remote sensing and numerical weather data, and collaborate with UK and African partners to operationalize solutions. Work within an end-to-end forecasting team on Project Cumulus, publishing results and supporting in-country testing.
Lead the development and deployment of cutting-edge generative AI systems for cybersecurity, focusing on large language models and deep learning at scale. Drive research strategy, build production-ready AI solutions processing trillions of daily events, and provide technical leadership across cross-functional teams. Contribute to AI innovation through publications and thought leadership while shaping best practices in responsible AI adoption.
Lead the research strategy for applying AI to cybersecurity, focusing on generative AI, large language models, and deep learning. Develop production-ready AI systems at scale, mentor research teams, and drive innovation in reasoning, summarisation, and interactivity. Contribute to technical standards and represent the company through publications and thought leadership.
