This role involves owning full-solution validation, minimizing time to production, and ensuring Day 2 stability for large-scale GPU clusters. You will work closely with customers, partners, and cross-functional teams to architect, implement, and optimize Kubernetes-based platforms and HPC systems.
This role involves owning full-solution validation, minimizing time to production, and ensuring Day 2 stability for large-scale GPU clusters. You will work closely with customers, partners, and cross-functional teams to architect and implement Kubernetes-based platforms, automate processes, and provide consultative guidance across the entire stack.
Design and deploy production-grade machine learning systems for high-impact clients in national security and AI safety. Work across the full ML lifecycle, from prototyping to scalable deployment, using cloud infrastructure and modern MLOps practices. Collaborate with cross-functional teams to deliver secure, reliable AI solutions that solve real-world challenges.
This role involves managing small molecule drug discovery programs, facilitating collaboration between the Cambridge and London offices, and supporting the DDMR team with program planning, risk management, and stakeholder communication. The position requires a strong background in drug discovery and program management, with a focus on integrating AI and ML technologies.
Lead and strategically guide a team of 25 medicinal chemists in redefining drug discovery through deep integration with AI. Shape the scientific direction of projects from hit identification to candidate nomination, while fostering collaboration with AI, biology, and pre-clinical teams. Drive innovation by challenging traditional approaches and embedding an AI-first culture across drug design workflows.
This role involves deploying and integrating generative AI models into pharmaceutical and biotech customers' scientific workflows. The engineer will lead technical scoping, build production-grade API integrations, and ensure seamless deployment within enterprise environments. They will also act as a technical liaison, gathering feedback to inform product and research improvements while working on-site with international partners.
A Research Engineer on the Pretraining team will bridge cutting-edge AI research and large-scale systems engineering, focusing on advancing large language models through work in model architecture, training optimization, and data processing. The role involves deep collaboration across research and engineering, with hands-on contributions to the full stack—from low-level infrastructure to high-level model design. Key projects include optimizing attention mechanisms, scaling distributed training, and improving model interpretability.
This role involves developing and deploying machine learning models for financial market predictions, building AI systems to extract information from financial documents, and contributing to data infrastructure. The position requires a strong quantitative background and experience in machine learning, statistical modeling, and data engineering.
Lead and shape the strategic direction of AI transformation programmes within the banking sector, working closely with C-suite clients to deliver impactful, responsible AI solutions. Build and grow a specialised banking practice by combining deep industry knowledge with technical excellence, driving both sales and delivery of high-impact projects. Mentor teams, influence industry thinking, and maintain executive confidence across complex, regulated environments.
This senior researcher role focuses on advancing AI safety through cutting-edge research, implementing robust safety measures in AI models, and collaborating with cross-functional teams to ensure the highest safety standards. The role involves setting research directions, evaluating model safety, and addressing adversarial and privacy risks.
This role involves identifying and mitigating emerging AI safety risks, developing new methodologies, and collaborating with experts across various domains to ensure the safety and alignment of OpenAI’s AI systems. The researcher will play a critical role in defining best practices and evaluating the robustness of safety systems.
Lead and grow a technical program management function for Wayve's AI Platform, driving delivery across data and compute infrastructure, model development tooling, training systems, and embedded inference optimisation. Partner with engineering leadership to accelerate developer velocity, improve compute efficiency, and ensure reliable platform performance in a fast-paced, innovative environment focused on embodied AI for autonomous vehicles.
This role involves leading a team of Applied AI Architects to drive the adoption of Anthropic's AI products across Europe's fastest-growing tech companies. Responsibilities include managing the team, setting pre-sales standards, working with high-value customers, and aligning cross-functional stakeholders.
This role involves building and deploying full-stack applications that integrate AI-driven physics simulation models to solve complex engineering problems for clients across aerospace, energy, automotive, and other advanced industries. You'll work closely with customers on-site and collaborate with data scientists and engineers to design, prototype, and iterate tools that transform engineering workflows. The position emphasizes end-to-end ownership, rapid development, and translating real-world engineering challenges into impactful software solutions using modern cloud-native technologies.
Design and build end-to-end applications that integrate AI-driven physics models into real-world engineering workflows. Collaborate with customers and technical teams to prototype, deploy, and iterate tools that solve complex engineering challenges across industries like aerospace, energy, and semiconductors. Work across the full stack with a focus on backend services, cloud infrastructure, and customer-driven product development.
