Top Tech Jobs & Startup Jobs in London

The Staff Machine Learning Engineer will lead the execution of ML systems, ensuring reliability and scalability while collaborating with cross-functional teams to deliver high-quality AI solutions.

The role involves building end-to-end production-grade ML systems, optimizing pipelines, integrating models into applications, and maintaining data systems.

The Technical Lead, Applications oversees application architecture, ensuring reliability and integration of AI into backend, mobile, and desktop services, while leading a senior engineering team.

As Technical Lead, you'll own ML system execution, manage data pipelines, model deployment, and ensure performance under real-world conditions while collaborating with the team.

Responsible for building and maintaining Android applications with AI features. Focus on performance, UX design, and collaboration with backend and ML engineers.

The VP of Research, Machine Learning will lead the research direction for AI systems, focusing on intelligence design, evaluation frameworks, and advanced machine learning techniques while ensuring real-world applicability.

The Head of Engineering will drive execution, structure workflows, ensure reliable delivery of engineering projects, and build a high-performing global engineering team.

The Senior Machine Learning Engineer will build core ML systems, handle data preparation and iteration, debug model issues, and ensure reliable production performance while mentoring other engineers.

As an iOS Developer, you will build and maintain AI-powered iOS applications focusing on performance, reliability, and user trust. Collaborate with engineers to integrate AI features, design UX patterns, and optimize app performance.

The Applied AI Engineer will develop and deploy AI features, enhance model performance, optimize systems for reliability, and collaborate with teams to address complex problems.