Lead the development of next-generation AI systems for cybersecurity, focusing on large language models and deep learning at scale. Design and implement production-ready AI solutions that process trillions of events daily. Provide technical leadership, mentor research teams, and shape AI strategy while driving innovation in reasoning, summarisation, and interactive systems.
This role involves owning the technical vision and architecture for a data enrichment platform that processes petabytes of driving data. You will lead the development of backend services, APIs, and workflows, while collaborating with multiple teams to ensure scalability, reliability, and cost efficiency.
This role involves designing and evolving scalable data pipeline and orchestration infrastructure to support Wayve’s autonomous driving systems. The engineer will revamp the existing Harness system and build a new DAG-based workflow platform to handle high-volume data from vehicle fleets and external sources. The position emphasizes reliability, efficiency, and usability across distributed data processing, batch inference, and incident response workflows.
Lead technical initiatives to enhance workplace technology and automation across dunnhumby, focusing on Microsoft 365, AI-driven workflows, and integration with platforms like ServiceNow. Design automation solutions using PowerShell, APIs, and infrastructure-as-code while promoting Copilot adoption and scalable operational improvements. Act as an internal consultant to guide teams in agile delivery and practical implementation of enterprise-grade tools.
Lead a full-stack engineering team building a modern, AI-driven platform for real-time customer data science in retail. Focus on scalable cloud-native systems using .NET, Python, React, and Terraform, with strong emphasis on code quality, CI/CD, and cross-team collaboration. Drive technical direction while mentoring engineers and shaping platform architecture across GCP and Azure.
This PhD studentship focuses on developing adaptive large language models that learn efficiently from limited data by leveraging linguistic structure. The research will design AI architectures that allocate resources based on a language’s grammatical and typological complexity, rather than corpus size, and will be tested across diverse low-resource languages. The candidate will collaborate with native speaker communities to ensure cultural appropriateness and robustness beyond standard metrics.
This role involves leading research in privacy-preserving generative AI, focusing on techniques like differential privacy, federated learning, and secure inference. The scientist will design and validate machine learning models, translate research into deployable systems, and contribute to publications and collaborations within a multi-partner environment. Emphasis is placed on responsible AI, reproducibility, and mentoring junior team members.
The AI Accelerator Lead will establish and drive a strategic initiative to unlock enterprise-wide value from AI, combining technical leadership with programme-level influence. Responsibilities include designing and operating the AI Accelerator, exploring advanced AI techniques, and building high-impact prototypes that evolve into scalable solutions.
Lead the design and delivery of large-scale AI and data transformation initiatives in high-assurance sectors such as security and justice. This role involves guiding AI solutions from proof of concept to secure, production-grade deployment, with a focus on technical architecture, governance, and cross-functional leadership. Requires deep expertise in generative AI, LLMs, and cloud-based MLOps in regulated environments.
Design and operate scalable cloud infrastructure for AI and agentic systems, with a focus on model serving and production reliability. Build cloud-native solutions using GCP technologies and support scientists with robust, high-performance services. Work across the full software lifecycle in an agile environment alongside ML engineers and domain experts.
Build secure, auditable systems for handling lawful data access requests, translating legal and operational requirements into reliable technical workflows. Design backend services, data pipelines, and approval interfaces with strong privacy, least-privilege access, and full lifecycle auditability. Collaborate closely with Legal and Operations to improve accuracy, efficiency, and operator experience in high-stakes compliance processes.
Lead and grow a product design team focused on enterprise AI applications, shaping human-AI interaction patterns for high-stakes decision-making environments. Drive design strategy from problem scoping to delivery, ensuring intuitive, research-backed experiences for expert users. Contribute to a shared design system while raising the craft standard across a distributed team.
This internship involves hands-on work on real projects, including building reinforcement learning pipelines, developing evaluation infrastructure, and creating fraud-detection systems. Interns will work closely with experienced engineers and contribute to impactful AI applications.
This role involves designing and delivering secure CI/CD pipelines, building and supporting Kubernetes/container platforms, and embedding security controls into engineering workflows. You'll work closely with data and AI teams to improve platform reliability and deployment standards, with a focus on DevSecOps and automation.
Lead the engineering team behind Multiverse's Diagnose & Prescribe (D&P) system, which assesses skill gaps and guides learners and employers to the right apprenticeships. You'll own technical direction, team health, and delivery across AI-driven services including RAG, LLM-scored assessments, eligibility logic, and onboarding flows. Work closely with Product, Design, and GTM to shape an AI-native platform while evolving services out of a legacy monolith.
