Top Machine Learning Jobs in Edinburgh

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

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.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Leads the FCA’s Agentic AI and Data Science Research function, setting AI strategy, governance, research ethics, data science standards, and long-term capability roadmaps. The role directs horizon scanning, responsible AI adoption, model assurance, and advanced analytics initiatives supporting regulation, financial crime reduction, and organisational effectiveness. It provides senior technical advice, leads multidisciplinary teams, develops talent, and influences executive, board, regulatory, and technology stakeholders.

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.

Develop and optimize machine learning and generative AI solutions for digital agents, including LLMs, NLP, RAG, retrieval, experimentation, evaluation, and statistical analysis. Build scalable data and ML pipelines using Python, SQL, and Spark; assess model quality, reliability, safety, and business impact; and support production deployment. Collaborate with engineering, product, and data science teams while mentoring less experienced colleagues.

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.

Guide clients through Cordial platform implementations, third-party integrations, API and JavaScript integrations, data modeling, dynamic scripting, and machine learning capabilities. Serve as a technical subject matter expert, resolve complex issues, manage projects and stakeholder expectations, document solutions, and collaborate with Product, Engineering, Client Success, Support, Strategy, Sales, and partners to drive adoption and successful client outcomes.

Manages science and technology initiatives for sustainable industrial fisheries. Leads multidisciplinary projects involving electronic monitoring, AI, machine learning, computer vision, data systems, hardware, software deployment, and seafood traceability. Oversees vendors, contractors, budgets, procurements, technical assessments, and deployment of systems in remote environments. Translates technical concepts for diverse stakeholders and supports technology evaluation, scaling, and conservation strategy. The role may require domestic and international travel of 25% or more.

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.

Own the vision, roadmap, development, launch, and continuous improvement of an AI chatbot. Responsibilities include market and competitive research, requirements gathering, stakeholder coordination, UX collaboration, NLP and machine learning enhancement, performance analysis, go-to-market planning, user adoption, and product iteration. The role also requires customer engagement, software sales knowledge, automotive market familiarity, strong communication, negotiation, and technical aptitude.

Conduct and publish original research in artificial intelligence, digital manufacturing, robotics, digital twins, and related engineering disciplines. Develop and deliver undergraduate, postgraduate, and continuing professional development teaching. Supervise PhD students, contribute to curriculum development, pursue research grants, engage with industry and policy partners, and support university management, enterprise, knowledge transfer, and inclusion initiatives.

Lead EMEA communications strategy for a global B2B technology client. Develop integrated, social-first plans connecting paid, owned, earned, influencer, partnership, and offline activity. Translate complex product narratives into customer-focused messaging, creative briefs, presentations, and campaigns. Manage regional and global stakeholders, agencies, and production partners while supporting execution, localization, performance optimization, and brand consistency. Use GenAI and automation to accelerate creative development and improve marketing workflows.

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.

Leads and develops a team of Data Scientists and other Data professionals, setting strategic direction and identifying high-impact opportunities. Partners with Product, Engineering, and senior stakeholders to shape product strategy and influence decisions through experimentation, causal inference, statistical modelling, machine learning, and analytics. Ensures analytical work drives measurable customer and commercial outcomes while collaborating with other data disciplines on tooling and infrastructure. Also contributes to hiring, coaching, technical standards, and the broader Data Science practice.

Lead a financial crime data science team focused on detecting, preventing, and mitigating financial crime. Partner with Product, Risk, Engineering, and control owners to shape data strategy, generate strategic insights, improve product decisions, and deliver rigorous analytics and machine learning solutions. Hire, develop, and retain data scientists and analysts while supporting innovation through business intelligence, experimentation, causal inference, and self-serve analytics.

Lead real-world evidence biostatistical analyses using large-scale healthcare data to support clinical development, regulatory strategy, HEOR, and payer decisions. Design observational studies and target trial emulations, apply causal inference, statistical learning, machine learning, and NLP, and build reproducible Python/R workflows. Collaborate with clinical, epidemiology, data engineering, and HEOR teams while translating findings for technical and non-technical stakeholders. Support regulatory submissions, governance, audits, and scientific dissemination.

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

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.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Drive end-to-end B2B sales of Data and AI consulting services in the US market. Responsibilities include prospecting, pipeline generation, solution selling, account planning, business-case development, executive stakeholder engagement, partner collaboration, and closing enterprise and mid-market opportunities involving Databricks, Lakehouse modernization, data engineering, analytics, AI/ML, and GenAI.