Top Machine Learning Jobs in Glasgow

Design and implement security solutions for machine learning models on embedded hardware, focusing on secure execution environments and model protection features.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

As a Machine Learning Engineer, you'll develop production-ready data solutions, enhance financial data, optimize algorithms, and collaborate with product teams to deliver robust code.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The role involves designing secure AI/ML systems for edge devices, addressing security threats, regulatory requirements, and communicating effectively with stakeholders.

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

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.

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

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

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