Top AI Jobs in London

As a Staff Machine Learning Engineer at Mozilla, you will lead the integration of Generative AI solutions in Firefox, develop infrastructure for model training, and optimize deployed models while mentoring junior engineers.

The Staff ML Engineer / ML Team Lead at Zencoder will lead the development of AI-driven solutions, focusing on AI pipelines and models for code generation and refinement. Responsibilities include creating embedded AI agents, collaborating with teams, testing solutions, and staying updated on industry trends.

Develop and monitor AI/ML models for analyzing blockchain data, collaborating with teams to enhance Nansen's platform and user experience. Mentor junior engineers and align AI initiatives with business goals.

Lead the implementation of AI-powered features, develop frontend experiences, optimize backend services, and mentor junior engineers while focusing on design and user satisfaction.

The Senior Software Engineer will develop and scale the Datafold Migration Agent, focusing on AI-driven SQL translation and data comparison, while managing projects end-to-end and making strategic decisions for scalability and performance.

Support the development and deployment of AI solutions, gain exposure to machine learning and natural language processing, and collaborate on AI capabilities integration.

The AI Data Engineer will develop scalable data ingestion pipelines and optimize distributed architectures for generative video models using high-quality data.

As a Software Engineer (AI), you'll develop applications that utilize machine learning, particularly integrating large language models, while collaborating with backend and ML teams.

Lead the design and scaling of data pipelines for generative video models, ensuring data quality and efficient processing. Oversee a team of data engineers and collaborate with various stakeholders.

The Senior Full Stack Engineer will develop applications using AI and cloud technology, manage databases, and collaborate on impactful projects.

Lead development of AI-powered applications, integrate with tools, optimize workflows, and enhance DevOps practices in a fast-paced environment.

Develop and implement AI/ML models to solve business problems, ensuring production deployment, reliability, and data analysis. Collaborate with teams and manage project blockers.