Top Machine Learning Jobs in Edinburgh

Provide clinical guidance across sales, implementation, product, and support teams for InterSystems health information solutions. Engage senior clinical and executive stakeholders, lead demonstrations and workshops, support procurement and digital transformation, and translate clinical requirements into solution narratives to drive adoption and product strategy.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

Lead the creation of user-centric digital products in financial services, focusing on intuitive design and leveraging AI for enhanced user experiences.

Lead and grow a distributed engineering organization building customer-facing security capabilities: proprietary scanners, AI/ML detection engines, agentic remediation, vulnerability management, and security foundations. Set vision and roadmap, drive architecture and delivery, partner with product management, establish engineering standards, and represent the group in cross-functional and customer forums.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

As a Junior Quantitative Trader, support trading activities, analyze algorithm performance, improve trading workflows, and assist with compliance and risk management.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and manage an ML engineering team building post-origination credit models for repayment, collections, recovery, and loss mitigation. Define technical strategy, design and scale ML solutions, partner with product, engineering and risk, mentor engineers, and operationalize models to minimize loan loss and personalize collections.

Lead product strategy and transformation for Funds Middle Office, coordinating cross-functional Agile programs, deploying data and AI capabilities, improving IBOR/ABOR and operational workflows, engaging senior stakeholders, and delivering scalable client-facing solutions.

Design, develop, and maintain the core backend of a cloud-based distributed video management system. Build new features, increase capacity, manage CI/CD and customer deployments, and ensure code quality, security, and scalability while collaborating within an agile team.

Lead the development and optimization of machine learning algorithms, owning the end-to-end model development and collaborating with Data Engineers for integration into live systems.

The role involves designing scalable data pipelines, implementing custom ML algorithms, and working on microservice architectures for ad optimization models.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

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.

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.

Lead development of enterprise commercial intelligence: build data models (pipeline, forecasting, segmentation), deploy AI/ML for forecasting and churn, create dashboards, establish data governance, partner with senior leaders to drive insight-led decisions and adoption across global teams.

The Applied Machine Learning Scientist will innovate and implement ML algorithms to enhance advertising performance, collaborate with engineers, and prototype in data-driven models.

Lead statistical planning and delivery for clinical studies using R and RShiny, mentor biostatistics staff, prepare SAPs and programming specifications, perform quality control, support submissions and regulatory interactions, and develop/maintain R-based visualization apps and infrastructure.

Drive end-to-end product design for Avid Content Core, representing the customer to define and prioritize product stories, collaborate with engineering on implementation, integrate AI into SaaS offerings, engage customers and partners, and ensure workflows, deployment, security, and quality throughout the agile development lifecycle.

The Factory Software Engineer will implement technology solutions for data integration, collaborate with stakeholders, and ensure delivery of high-quality software solutions.

The Research Manager will lead AI-powered insight projects, manage client relationships, oversee team execution, and innovate using AI tools to improve insights delivery.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.

Lead market pricing for the UK pet insurance book: develop demand, elasticity, and price-optimisation models, monitor competitors and market trends, make rate recommendations, present findings to stakeholders, support pricing strategy, and line-manage one pricing analyst.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

Lead design, development, and production deployment of scalable, secure Data & AI solutions on Databricks and Microsoft Foundry. Define AI technical roadmap, mentor an AI engineering squad, partner with stakeholders to prototype and scale use cases, and enforce AI governance, security, and ethical practices.