LocationRemote working (anywhere in the UK)Salary: £78,000 to £85,000 (including a £10,000 market rate allowance), plus a further £5,000 for candidates based in London.About the jobJob summaryThis post is open to applicants who can meet the College’s nationality, UK residency...
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
Design and operate a secure, scalable AI platform infrastructure, building CI/CD pipelines and deployment workflows in collaboration with data science and engineering teams. Focus on observability, automation, and high availability using cloud-native technologies. Support AI workload deployment and agent infrastructure with a strong emphasis on performance, cost efficiency, and security.
This role involves configuring and optimizing Databricks-based ML development and deployment frameworks, implementing model training and deployment capabilities, and building CI/CD pipelines for ML lifecycle management. You will lead the technical implementation of pilot models and develop reusable migration accelerators on the Global AI Platform.
This role involves owning and developing the MLOps infrastructure for a growing AI platform, building and maintaining orchestration pipelines, deploying ML workloads on Kubernetes, and implementing CI/CD and monitoring systems. You will work closely with Data Scientists and ML Engineers to scale deployments and support real-world impact.
Develop and optimize scalable AI/ML infrastructure solutions on NVIDIA platforms, supporting both internal and external customers. Focus on MLOps pipeline development, distributed training, inference optimization, and deep-stack performance tuning across hardware and software layers. Contribute to open-source tools and collaborate with engineering teams to enhance AI frameworks and cloud integrations.
This role involves building and deploying custom AI solutions on cloud platforms, with a focus on MLOps pipelines, distributed training, and inference optimization. The engineer will act as a technical advisor for internal and external customers, diagnose full-stack AI/ML system issues, and contribute to open-source tools and reference architectures. Work includes performance profiling, supporting new hardware in frameworks, and collaborating on scalable AI infrastructure.
This role involves designing, developing, and operating modern AI platforms and MLOps systems, focusing on Python ecosystems, Kubernetes, and MLOps tooling. You will work in a specialist team on a significant AI and MLOps transformation programme, collaborating across development, platform engineering, and operational teams.
This role involves designing and maintaining cloud-native infrastructure and Kubernetes environments to support large-scale AI and machine learning workloads. You'll use Terraform for Infrastructure as Code and collaborate closely with engineering and data science teams to optimise deployment workflows and platform performance. The position focuses on building scalable, secure, and observable platforms for AI in a high-visibility environment.
This role involves designing and maintaining scalable MLOps infrastructure, deploying and managing machine learning models on Azure, and building CI/CD pipelines. You will work closely with engineering and delivery teams to ensure platform reliability and support the adoption of AI solutions.
This role involves working on a large-scale, modern technology environment, designing, building, governing, and operating data and ML platforms. Opportunities span architecture, engineering, security, operations, and service delivery, catering to both hands-on technical specialists and experienced leaders.
This role involves designing, developing, and deploying AI/ML applications using Python, PyTorch, and GCP. You will build and integrate generative AI solutions, containerize and serve machine learning models, and implement CI/CD pipelines and model monitoring. Collaboration with engineering teams and stakeholders is key.
This role involves designing, developing, and deploying secure AI and ML solutions for autonomous and mission-critical systems. Responsibilities include building machine learning models, supporting autonomous capabilities with ROS 2, and ensuring adherence to Responsible AI and safety standards.
This role involves designing and governing high-stakes AI systems for public sector clients, with a focus on responsible AI, model evaluation, and production MLOps. The engineer will establish technical standards, lead incident resolution for model safety, and build reusable AI capabilities like fine-tuned models and agent architectures. They will also mentor senior engineers, advise on technical roadmaps, and act as a trusted advisor to government clients on AI strategy and deployment.
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.
This role involves designing, building, and deploying high-performance Machine Learning solutions, working across the full ML lifecycle from experimentation to production. You'll collaborate with engineering and AI teams to ensure robust MLOps practices and optimize model performance in production environments.
Design and implement production-grade AI and ML systems, focusing on Agentic AI, RAG, and LangChain/LangGraph patterns. Establish engineering standards, improve observability and model risk controls, and drive adoption across engineering teams. Work within a regulated environment to enable safe, scalable AI solutions in production.
