Top Machine Learning Jobs in Edinburgh

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

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.

Lead enterprise sales for Everpure's AI/HPC data infrastructure, driving large deals with F1000 companies. Build executive relationships, lead cross-functional pursuit teams, influence product roadmap, manage a pipeline to exceed revenue targets, and evangelize all-flash storage and data pipeline solutions for AI workloads.

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.

Design and validate agentic AI capabilities for Protege in PatentSight using ML, NLP, and LLMs. Build retrieval and hybrid search strategies, run experiments, evaluate models, analyze large IP datasets, and translate results into product recommendations while collaborating with engineers, product, and IP experts.

Own product messaging, positioning, and competitive intelligence for PolyAI voice assistants. Define go-to-market strategy, develop personas and sales enablement collateral, drive demand and analyst relations, run customer research, maintain competitive databases, scale the product marketing team, and represent the company externally.

Lead development and implementation of analytics and predictive models to support R&D Quality oversight across clinical, safety, laboratory, and vendor data. Build dashboards, risk indicators, automated monitoring, and audit-support tools; integrate complex data to identify portfolio-level risks and translate findings into actionable quality recommendations that support GCP/GVP/GLP/GCLP compliance and inspection readiness.

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

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.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Lead identification, development, and global deployment of AI and automation solutions to optimize forms and precedents content operations. Prioritize opportunities, collaborate with cross-functional teams, ensure governance and quality, integrate solutions, report outcomes to leadership, and drive continuous improvement and responsible AI practices.

As a Lead Data Scientist, you will set technical direction, ensure project delivery, manage client relationships, and mentor data scientists.

The Computer Vision Engineer will lead AI initiatives in the defense sector, delivering solutions and mentoring teams while driving technical strategy and capability development.

Create clear, customer-focused documentation and help content for cloud-based video security, access control, and intrusion platforms. Design user-centric guides, peer-review content for quality and consistency, and collaborate with Engineering, Support, Escalations, and UX teams to improve documentation and product usability.

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 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.

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.

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.

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.