Top Machine Learning Jobs in Edinburgh

Lead applied AI research and architecture for GenAI in cybersecurity: design LLM architectures, implement production-grade deep learning systems at scale, mentor scientists, set technical standards, and align AI strategy with business goals.

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 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.

Lead design and delivery of secure, scalable enterprise software for private banking. Build reusable frameworks, integrate AI/ML, ensure operational stability, mentor engineering teams, and influence senior stakeholders to drive digital transformation.

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.

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.

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.

The VP of AI Platform Engineering will lead AI development at BlackRock, focusing on scalable architecture, team management, and cross-functional coordination to enhance engineering capabilities and empower technologists.

Lead a team of data scientists to build and maintain data pipelines, clean and transform data, develop statistical and machine learning models, deliver predictive analytics, and partner with stakeholders to drive business value and governance.

Lead development of a modern first-line technology control environment, embedding automated, preventative and real-time controls across cloud-native platforms. Partner with Technology, Data and AI teams to support resilience, cloud migration and platform transformation. Use data-driven monitoring to improve control effectiveness, influence senior leaders, and build a high-performing Control Office team.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

Lead and develop a team of ML specialists to deliver production ML systems for fraud and financial crime. Set priorities, ensure model lifecycle practices (development, deployment, monitoring, governance), partner with Product, Risk, Engineering and Data, and raise standards for performance, explainability, reproducibility and observability while building an inclusive high-performing team.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

Lead technical research and advisory work on technologies underpinning online services to support Ofcom's online safety objectives. Provide expert technical guidance on AI/ML moderation systems, encryption, privacy, and network architectures; design and manage research projects and experiments; assess regulatory feasibility and platform implications; produce analytical outputs for senior decision-makers; and build internal and external relationships to inform policy and regulatory approaches.

Transform operational data into actionable insights by building semantic models, reporting solutions and metrics (Power BI/Fabric, DAX, M, SQL). Ensure data quality, governance, access controls, troubleshooting, documentation, and stakeholder collaboration to enable self-service analytics.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Identify, qualify, and nurture enterprise leads for Cohere's AI solutions through outbound outreach, BANT qualification, Salesforce pipeline management, and collaboration with marketing. Run smaller sales cycles to close opportunities and stay current on industry and product trends.

Define and lead the enterprise AI operations model and governance. Own operational performance, monitoring, adoption, reliability, and business value of AI products. Drive cost transparency and optimisation across Azure, Databricks and inferencing. Govern model lifecycle (onboarding, deployment, monitoring, retraining, upgrades, retirement) and lead incident, change, resilience, and responsible AI processes to keep production services secure and compliant.

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.

Lead data visualisation and reporting strategy: design interactive dashboards, standardise metrics, modernise executive reporting, embed visualisations into SaaS products, develop data storytelling frameworks, translate complex analytics into actionable narratives, and train teams to drive insight adoption across the organisation.

Design, build, and productionise end-to-end ML and GenAI systems (retrieval, ranking, LLM conversational components) for personalised product recommendations. Develop evaluation frameworks for LLM outputs, integrate monitoring and experimentation pipelines, and partner cross-functionally to deliver production-ready solutions and best practices.

Designs and deploys supervised machine learning classifiers using curated patent data, conducts desk research on technologies, scopes and defines client classifier taxonomies, supports customer meetings and data review, and delivers ad-hoc analysis and presentations as projects progress.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.