Top Tech Jobs & Startup Jobs

Lead the learning science discipline: define learning goals, skill models, adaptivity and feedback; create a Learning Science Playbook; design rigorous evaluations; partner with product, data science and engineering to embed pedagogically sound, measurable AI-driven learning systems; contribute to safety and assurance; mentor colleagues and represent Faculty externally.

Lead and develop product and service design within Applied AI, deliver high-impact client engagements, build design capability, define skill frameworks, and partner with business development and executive stakeholders.

As a Senior Manager, you will oversee project delivery, manage customer relationships, identify business opportunities, and mentor teams in AI applications.

Lead commercial growth for Energy Transition & Environment accounts by managing client relationships, driving multi-million-pound sales, overseeing cross-functional delivery teams, identifying AI-driven use cases, negotiating complex deals, and representing Faculty at industry events.

The role offers veterans a one-week unpaid placement to learn about AI and data science in a leading UK tech company.

Lead design of AI-native, high-impact user interfaces for Defence clients. Run user research, produce wireframes, prototypes and detailed designs, evolve design systems, ensure accessibility, mentor designers, and communicate design rationale to stakeholders and clients.

As a Senior Machine Learning Engineer, you will lead the development of AI systems, design production-grade ML software, and mentor junior engineers while engaging with clients on technical strategies.

Lead design, build and deploy production-grade ML systems and infrastructure. Make architecture decisions, implement best practices for ML at scale, advise clients, collaborate cross-functionally, and mentor junior engineers while meeting operational and ethical standards.

Lead technical direction and delivery of large-scale AI/ML platforms. Architect microservices and shared libraries, align ML, data science and DevOps, coach distributed engineers, define production readiness, and drive hiring and standards across software engineering.

Lead technical direction and delivery of large-scale, production ML systems. Design and implement scalable model deployment, lifecycle management, CI/CD, APIs, testing and versioning frameworks. Oversee multiple complex workstreams, justify architectural decisions to stakeholders, coach engineers, and recommend new AI technologies to maintain competitive advantage in high-risk environments.