Top AI Engineer Jobs in London

The Applied AI Engineer will support customer adoption of AI products, integrate AI models into applications, and improve product capabilities based on feedback.

As an AI Engineer at Elixirr, you will design and implement AI systems, collaborate with teams, drive innovation, and deliver impactful AI solutions.

As an AI Engineer, you will develop and maintain AI platforms and SDKs, deliver workflows for research, define best practices, and embed in business teams to explore new AI opportunities.

The role involves building AI connectors, developing automation platforms, and collaborating to enhance workflows using AI in a fintech environment.

The Applied AI Engineer will onboard customers, deploy AI applications, and collaborate with teams to resolve technical challenges and drive technological transformation.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Design and deliver complex product features using AI tools, build AI-native workflows, and mentor teams to enhance engineering practices.

The AI Engineer will design and optimize transformer architectures, fine-tune large language models, implement prompt engineering strategies, and collaborate on AI solutions with cross-functional teams.

The Data/AI Engineer will design scalable data pipelines, model data, develop AI-driven solutions, and collaborate with teams to optimize operational workflows across international entities.

Build and deploy AI systems for investment insights, focusing on ML and LLM-driven solutions, while ensuring high-quality data flow and outcomes.

As an AI Engineer, you'll develop and enhance ML products, focusing on NLP and cloud-based solutions while collaborating with experts to innovate in regulatory compliance.

Lead the development of voice AI solutions focusing on speech recognition, NLP, and deployment of AI models. Collaborate with teams to deliver high-quality products and innovative technologies to enhance customer experiences.

As an AI Product Engineer, you'll build and support AI-powered tools, oversee client technical delivery, and collaborate with cross-functional teams to design and implement solutions.

Lead the design and development of AI solutions for clients, implementing language models and frameworks, mentoring engineers, and evolving internal AI platforms.

The Principal AI Engineer will define AI architecture, lead teams, develop solutions, and mentor engineers to enhance enterprise AI systems.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

The AI Infrastructure Engineer will build and optimize training pipelines and inference services for AI models, enhance GPU-level performance, and mentor team members.

As the first full-time engineer, you'll transform a prototype into a SaaS by developing backends, designing user interfaces, and implementing security standards.

Design, build, and deploy machine learning models and intelligent data systems for Formula 1, focusing on predictive analytics, computer vision, and natural language processing, while collaborating across teams to identify data opportunities.

Lead the development of AI models for drug discovery, optimize performance, collaborate across teams, and drive innovation in healthcare.

Join Watershed's sustainability AI reporting team to prototype, build, and productionize AI features (LLMs, embeddings) for information extraction and report generation. Ship production-ready, well-tested full-stack code and keep systems current with state-of-the-art AI to deliver customer-facing product features.

Design, implement, and optimize AI/LLM workflows and infrastructure. Collaborate across teams to integrate models into production, document best practices, and optimize performance and costs.

Design and build scalable microservices, APIs, and data pipelines for high-dimensional simulation data. Implement data storage and ingestion for ML workloads, enable BI and visualization tools, own features end-to-end, maintain CI/CD and observability, and collaborate with data scientists to ensure secure, reliable, performant systems.

The role involves designing, developing, and supporting cloud and AI solutions primarily on Azure, including automation and integration components, while ensuring security and compliance.

The Senior Applied AI Engineer will develop scalable AI features, improve application reliability in production, and collaborate with teams for deployment of AI-driven services.