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.
Conduct foundational research to develop AI-driven physical simulation models for engineering and manufacturing applications. Translate complex physics and engineering problems into mathematical formulations, build and iterate machine learning models—particularly in neural operators, geometric deep learning, or generative modeling—and collaborate closely with engineers and customers to deliver real-world impact across advanced industries.
Develop and scale AI-driven physical foundation models for engineering simulation, bridging research and production. Translate scientific prototypes into robust, distributed ML systems using high-performance computing and cloud infrastructure. Collaborate closely with researchers, engineers, and customers to solve real-world physics and engineering challenges.
This role involves leading the design, development, and deployment of advanced AI solutions to enhance operational efficiency and support business growth. You will collaborate with senior stakeholders, guide technical direction, and mentor a team of engineers while ensuring systems are secure, scalable, and compliant.
This role involves building and optimizing ecommerce platforms, AI-driven customer communication agents, and automated workflows to enhance customer experience and business performance. You'll develop WordPress sites, integrate payment and booking systems, and implement AI solutions using OpenAI APIs, RAG, and vector search. The role emphasizes translating commercial needs into technical solutions, with a focus on measurable outcomes like conversion rates, lead generation, and operational efficiency.
Act as a commercial and delivery lead for high-stakes AI projects within the UK national security sector, bridging advanced AI research with government mission needs. Drive end-to-end project delivery, from scoping to implementation, while building trusted relationships with technical teams and senior stakeholders. Mentor teams, develop growth-focused proposals, and ensure responsible AI deployment in a fast-evolving landscape.
This role involves building and deploying production-grade machine learning systems for diverse clients, translating research into real-world applications. You'll work across the full ML lifecycle, design scalable software architectures, and collaborate with cross-functional teams to deliver impactful AI solutions. The position emphasizes technical leadership, cloud infrastructure, and best practices in ML deployment.
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.
This role involves leading the design and implementation of scalable, high-impact machine learning systems within complex enterprise and government environments, particularly in the defence sector. The Principal Machine Learning Engineer will act as a technical authority, shaping architectural direction, solving cross-project challenges, and mentoring engineering teams. Work includes strategic innovation, system integration, and hands-on technical leadership in ethical, real-world AI applications.
A Principal Designer will lead the development of product and service design disciplines within Faculty’s Applied AI division, delivering high-impact client projects while building design capability from the ground up. The role combines strategic client engagement with executive-level consulting, shaping multidisciplinary teams and embedding human-centred design in AI solutions. This position bridges technical AI outputs with real-world commercial outcomes across government, finance, retail, and other sectors.
Lead the development of the product management function within a high-impact AI consultancy, shaping standards and practices while delivering transformational AI solutions for enterprise clients. Work across technical, organisational, and strategic levels to bridge advanced AI models with real-world business outcomes. Operate in a hybrid role combining capability building, client advisory, and product execution.
This role involves developing and training advanced machine learning models for digital identity verification, with a focus on areas like deepfake detection, bias mitigation, document understanding, and efficient on-device ML. The candidate will conduct research, build multimodal models using synthetic data, optimise training performance across GPUs, and collaborate with engineering teams to deploy solutions globally. Work includes creating large-scale datasets, benchmarking vision-language models, and improving fairness in biometric systems.
This role involves leading project management for a multi-year osteoporosis drug discovery programme within a TechBio environment. You'll coordinate across interdisciplinary teams including wet lab biology, machine learning, and data science, translating scientific objectives into integrated delivery plans. The position requires managing cross-team dependencies, evolving workstreams, and governance processes in a discovery-stage R&D setting with high ambiguity and scientific complexity.
Develop and scale generative and predictive machine learning models for cellular behaviour using multi-omic biological data. Build robust distributed training and inference systems, bridging ML research and production deployment in close collaboration with scientists. Optimize performance across compute, memory, and I/O while advancing core ML infrastructure in a highly interdisciplinary environment.
