Top Machine Learning Jobs in Edinburgh

Deliver enterprise and operational risk transformation and advisory services for financial institutions. Assess and enhance risk processes, controls, governance, market abuse frameworks, and trade surveillance capabilities. Support AI-enabled analysis, surveillance model tuning, workflow automation, validation, auditability, and responsible AI practices. Collaborate with business, technology, compliance, and risk stakeholders to identify control gaps and implement data-driven improvements.

Perform malware and threat research across the attack lifecycle, validate and improve Falcon detections, collaborate with engineering and ML teams, automate analysis, support external security testing, and translate findings into product protections.

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.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Build AI and automation solutions using Microsoft Fabric, Power Platform, LLMs, intelligent document processing, agentic AI, and Power BI. Lead responsible AI practices, stakeholder discovery, training, adoption, and MVP delivery across capital project consulting. Maintain billable involvement in Technical Due Diligence engagements, identify client-facing AI opportunities, and support proposals and commercial delivery. The role requires Python, SQL, data pipeline development, governance awareness, strong communication, and UK work authorization.

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.

Conduct postdoctoral research on avian influenza modeling in cattle using multi-scale simulation models, machine learning, and demographic, environmental, and phylogenetic datasets. Collaborate with UK and US universities, coordinate research activities, contribute to disease-control strategies, disseminate findings, and participate in international visits and project meetings focused on infectious disease research.

Provide technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive modeling, and optimization. Design scalable AI platforms, APIs, services, data pipelines, and infrastructure; establish evaluation, testing, observability, security, and governance standards; optimize system performance, reliability, and cost; and partner with multidisciplinary teams to deploy and operate solutions. Mentor engineers and influence technical strategy across the organization.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Leads the architecture and delivery of complex Azure, Microsoft 365, cloud, and AI solutions for strategic customers. Translates business needs into secure, scalable architectures; manages requirements, design governance, technical quality, deployment, and stakeholder alignment. Acts as a trusted technical advisor, drives presales and delivery outcomes, develops reusable intellectual property, mentors architects, and promotes Microsoft technologies through thought leadership and customer engagement.

Lead a small team of engineers while remaining hands-on in Java backend development. Design scalable services and integrations supporting campaign analytics, attribution, automation, AI-powered recommendations, and intelligent decisioning. Guide architecture, reliability, observability, and technical planning; coach engineers; and collaborate with Product, UX, ML, and data science teams to deliver trustworthy AI experiences and evaluation mechanisms.

Lead technically complex product work on Rosso, embedding with ML, data science and engineering teams to turn business and customer needs into shipped features. Define success criteria for models/forecasts, manage edge cases and operational risk, and prioritize work across portfolio, forecasting, pricing optimisation and related systems.

Provides technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive models, and optimization. Establishes architecture, engineering standards, evaluation and observability practices, and reusable AI platforms. Partners across business, engineering, data, risk, and control teams to deploy and operate scalable systems while optimizing performance, reliability, security, and cost. Mentors engineers and influences technical strategy.

Leads the design and scaling of Databricks-based data, analytics, and AI platforms supporting global customer operations. Builds enterprise data pipelines, machine learning, NLP, generative AI, conversational AI, dashboards, and operational intelligence solutions. Establishes governance, data quality, CI/CD, reliability, and AI lifecycle standards while partnering with product, operations, engineering, workforce management, and AI teams. Provides technical leadership, coaching, and mentorship to engineers and data scientists.

Lead Mitek’s EMEA revenue strategy and execution across direct enterprise and channel sales for identity and fraud prevention platforms. Own regional growth, forecasting, pipeline, account expansion, partner ecosystem development, customer adoption, and revenue targets. Manage enterprise sales and account teams, negotiate complex multi-year agreements, support regulated-market customers, and report performance to the CRO while collaborating with Product, Engineering, Finance, Legal, Compliance, Customer Success, and global channel teams.

Serve as the technical SME for compliance automation, overseeing GRC control mapping, evidence collection, integrations, and continuous monitoring. Partner with engineering teams to embed compliance into workflows, support audits and framework rollouts, assign control ownership, reduce audit burden, and maintain audit readiness. Lead cross-functional initiatives and communicate compliance risks, control status, and progress to technical and leadership audiences. The role requires cybersecurity framework expertise, program management, cloud and API fluency, GRC platform experience, and familiarity with AI-enabled compliance workflows.

Reviews and evaluates engineering, infrastructure, and platform documents and work products for technical accuracy, completeness, clarity, consistency, and relevance. Provides structured feedback, identifies errors and gaps, compares technical approaches, and follows defined evaluation frameworks. Requires independent work, strong communication, analytical ability, and professional engineering judgment. The role is fully remote and supports varied technical evaluation projects as an independent contractor.

Lead technical strategy and architecture for personalization, search, and recommendation systems. Deliver scalable ML-powered features, mentor senior engineers, and improve engineering quality across cross-functional teams.

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.

Designs and delivers integrated customer data solutions supporting Thales UK’s digital and data strategy. Responsibilities include architecture design, data integration, proof-of-concept development, stakeholder engagement, technical documentation, data governance, solution oversight, and lifecycle management. The role supports UK Ministry of Defence data standards, collaborates with engineering and digital platform teams, evaluates emerging technologies, and develops secure data management and analytics solutions across complex defence environments.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, security, scalability, and failure handling. Integrate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, and human oversight while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own an AI investing product vertical end-to-end, including strategy, roadmap, technical design, delivery, metrics, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Embed regulatory requirements across KYC, monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and reliability controls while aligning compliance, operations, finance, treasury, and design.

Owns an AI neobank product vertical end-to-end, including strategy, roadmap, technical design, delivery, regulatory requirements, AI evaluation, reliability, and launch. Partners with engineering, compliance, operations, treasury, finance, and design across payments, remittance, insurance, wealth, and trading products. Must balance correctness, scalability, security, user experience, cost, speed, and regulatory constraints in high-consequence financial systems.

Owns roadmap execution and capability definition for an Agentic AI Platform. Translates AI platform strategy into requirements, prioritized roadmaps, reusable agent orchestration and lifecycle capabilities, governance controls, observability, and scalable platform patterns. Partners with engineering, architecture, data, security, legal, compliance, customer success, professional services, and customers. Measures adoption, reliability, safety, quality, cost, and business impact while balancing technical feasibility, security, compliance, and customer value.

Conduct mathematical and computational research on elastic and elasto-inertial turbulence in viscoelastic fluids. Develop and apply statistical and machine-learning methods to compare experiments with simulations, optimize simulation parameters, estimate polymer stresses, and investigate flow states across two- and three-dimensional regimes. Collaborate with researchers at the University of Edinburgh, University of Pennsylvania, University of Cambridge, and University of Vermont, with opportunities for international research travel.