Top Machine Learning Jobs in Glasgow

Lead and mentor an agile team to design, develop, secure, and operate scalable cloud-native applications using modern front-end tech and AI-assisted engineering practices; drive automation, code quality, resiliency, and operational stability.

Lead Software Engineer responsible for designing, building, and supporting cloud-native payments solutions end-to-end. Deliver secure, high-quality production code, drive CI/CD and automation, improve resiliency and security, and leverage AI to optimize development and operations.

Lead design, develop, and deliver secure, scalable software for the Corporate Investment Bank. Drive architecture reviews, troubleshoot and review code, automate remediation, promote CI/CD and resiliency practices, evaluate vendors, and foster engineering best practices and inclusive team culture.

Lead engineer to architect and deliver AI-driven workflows and real-time Java/Kafka trading platforms. Design, develop, optimize low-latency systems, ensure operational stability, drive SDLC and CI/CD, promote resiliency and security, and collaborate with global stakeholders.

Design, develop, and troubleshoot secure, production-grade software. Produce architecture and design artifacts, analyze large datasets, drive improvements in code quality and system architecture, and leverage enterprise AI-assisted tools while ensuring secure and responsible AI use.

Lead and deliver secure, scalable software solutions across multiple teams. Design architecture, produce production-quality code, troubleshoot systems, analyze large datasets, and provide technical leadership to regional and global feature teams while promoting agile practices and inclusive culture.

Lead solution architecture across functional, information, and technical domains for enterprise-scale Securities Services platforms. Design data models, integration, metadata, master data, and migration strategies. Apply AI/ML to architecture practices, ensure conformance to firm standards, participate in governance, evaluate vendors, and promote reuse, security, resiliency, and automation across agile teams.

Design, develop, debug, and maintain secure, scalable production code and architectures; analyze large datasets to improve systems, support CI/CD and application resiliency, and contribute to engineering best practices and team culture.

Lead and scale engineering teams building multi-tenant Voice AI, Agent QA, analytics, auto-learning, and workforce management platforms. Own architecture for high-throughput voice data systems, real-time pipelines, telephony integrations, optimization algorithms, and enterprise compliance. Recruit and develop senior engineers and managers, establish engineering standards, guide cross-functional roadmap alignment, and deliver reliable production systems across global geographies.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.

Lead engineering systems and teams for an AI chat application, focusing on backend, mobile, and desktop. Oversee strategy, architecture, integration, and high-impact technical decisions for reliable user experiences.

As a Principal Engineer at M&S, you'll drive technical strategy, influence architecture, and mentor engineers while delivering on personalization, search, and machine learning features in collaboration with cross-functional teams.

Build and scale AI-driven backend systems and infrastructure for retail intelligence: develop the AI chatbot, agents, tooling and MCP integrations, evolve data processing across AWS and bare metal, own features end-to-end, and mentor team members.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Lead development of ClickHouse's Python connector and SDKs, build integrations with orchestration and transformation tools, drive AI/LLM integration strategy for production data workflows, engage with open-source community, and collaborate across product and platform teams to deliver enterprise-grade data integrations.