Top Machine Learning Jobs in Edinburgh

The Machine Learning Engineer will develop ML and GenAI solutions, deploy algorithms in production, mentor teams, and drive data strategy initiatives while fostering a collaborative culture in the data science community.

As a Machine Learning Engineer, you'll design and implement ML and GenAI solutions, deploy algorithms, maintain data science products, and contribute to a collaborative team culture.

As Product Manager, lead AI/ML strategies for Accelerant's Risk Exchange platform, collaborating with teams to develop tools for risk management and decision-making.

The Senior DevOps Engineer will design, implement, and optimize ML/AI pipelines using Azure Databricks, ensuring AI models are production-ready and scalable.

As an AI/ML Engineer, you will design and develop AI-powered applications, integrate AI features into BPM systems, and collaborate with teams to improve operational efficiency through innovative AI solutions.

The Senior Machine Learning Engineer will enhance the RAG platform by delivering AI solutions, collaborating with teams on product features, mentoring, and maintaining system stability.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

The AI/ML Engineer will develop and implement ML systems for secure-code understanding, manage infrastructure for LLMs, optimize models, and conduct research.

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.

The role involves reviewing and improving AI solutions, providing architectural feedback, evaluating model quality, and ensuring production readiness of AI systems in a healthcare context.

As a Lead Machine Learning Engineer, you will guide technical direction and deliver innovative AI projects, ensuring architectural soundness and fostering team growth.

As a Machine Learning Engineer, you will design, build, and deploy ML systems, manage AI project methodologies, and support delivery with technical expertise, collaborating with cross-functional teams and stakeholders.

As a Principal Java Engineer II in the ML Core team, you will build and maintain machine learning components for Elasticsearch, collaborate with engineering teams, and ensure scalable and high-quality code. You'll lead projects from design to implementation while supporting the team and community.

Lead the development and deployment of AI systems, designing scalable ML software and infrastructure while mentoring junior engineers and advising clients.

The Senior Platform Engineer in Machine Learning at Monzo will design, maintain infrastructure for ML models, and work with various cloud technologies.

As a Senior Data Engineer, you'll design scalable data pipelines, collaborate with engineers and product teams, and evolve the architecture to support growth in users and data.

This role involves developing and deploying machine learning models for fraud detection, collaborating with teams to ensure customer safety and business impact.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

The Senior AI/ML Engineer will design and optimize scalable systems, productionize AI prototypes, solve performance issues, and collaborate with teams on innovative solutions.

The Machine Learning Engineer will build, refine, and optimize AI/ML prototypes while collaborating with teams on technical documentation, deployment, and model integration.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

Lead the Voice team at Rasa, focusing on mentoring engineers, driving processes, and delivering voice features while maintaining strong communication and async practices.