Top Machine Learning Jobs in Edinburgh

Supports enterprise sales by discovering customer requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value engagements. Acts as a technical lead and consultative advisor, educating customers on architecture and best practices. Collaborates with sales, product, professional services, partners, and customer success teams while developing AI-driven and agentic solutions for demonstrations and customer outcomes.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

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.

Conduct world-leading interdisciplinary research within the Decisions Cluster of the Leverhulme Centre for Algorithmic Life, examining how AI and algorithmic technologies transform decision-making. Develop research and funding plans, collaborate across disciplines, contribute to knowledge exchange and the research environment, support postgraduate research students, and undertake academic administration and citizenship activities.

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.

Conduct interdisciplinary research in physical intelligence, soft sensing, robotics, machine learning, and signal processing. Develop sensing and perception methods enabling robots to understand their body state and physical interactions, integrate them into robotic and mechatronic platforms, and perform extensive experimental validation. Collaborate across sensing, robotics, electronics, and AI while developing new research ideas within an ERC-funded project.

Leads Aegon Asset Management’s enterprise-wide AI strategy, advising executives, scaling AI pilots into production, establishing responsible AI governance, prioritizing use cases, driving adoption of Copilot and agent-based technologies, and managing specialist teams, investment priorities, and strategic partners.

Own analytics and measurement for HighLevel’s AI product portfolio, including instrumentation, feature KPIs, adoption and quality analysis, and experimentation. Establish measurement standards, address data gaps, interpret non-deterministic AI results, influence product roadmaps, and mentor analysts. Partner with product managers, engineers, analytics engineering, and experimentation leaders in a fast-moving B2B SaaS environment.

Leads the mid-market business development function, including team building, territory strategy, prospecting, negotiation, closing, pipeline management, and account acquisition and retention across pharma and biotech. Partners with marketing, strategy, and commercial operations on go-to-market execution. Represents the company at industry events and develops relationships with clinical trial sponsors while selling complex AI-powered SaaS solutions.

Own the vision, roadmap, and delivery of AI-powered functionality across the IRIS Elements Platform. The role involves researching customer needs, prioritizing product opportunities, launching scalable AI features, establishing evaluation frameworks, and collaborating with Engineering, Design, Data, and Commercial teams. The successful candidate will shape AI strategy, promote responsible AI practices, monitor market developments, and deliver measurable value for accountancy software customers.

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.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Own and build Oversee’s product marketing function, including ICP definition, positioning, persona messaging, competitive and win/loss research, product content, sales enablement, and end-to-end product launches. Partner closely with product, sales, growth marketing, and executives to translate technical AI and travel technology capabilities into compelling commercial messaging, establish repeatable GTM processes, and measure launch performance.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Lead the design, development, deployment, and maintenance of scalable cloud-native platform capabilities for Walmart Connect’s sponsored search ad server. Build infrastructure, tooling, AI/ML frameworks, and distributed systems; conduct design reviews; drive software lifecycle activities; mentor engineers; influence architecture and technical decisions; and collaborate across teams to translate complex business needs into reliable, data-driven solutions.

Build and improve Firefox WebCompat internal dashboards, reporting tools, and broken-site screenshot capture pipelines. The role involves creating reliable data views for triage and metrics, automating screenshot workflows, collaborating with WebCompat and QA teams, and translating reporting needs into effective tooling. Familiarity with WebCompat workflows, Bugzilla, screenshot automation, and machine learning is preferred.

Design, implement, and deploy efficient adaptive machine learning systems that retrain or fine-tune models using production data. The role combines applied research with production engineering, including data strategy, model evaluation, online learning, reinforcement learning, observability, and real-world product development. The engineer will own data products, solve novel technical challenges, and collaborate closely with the founding team on research and product direction.

Leads Tide’s global engineering organization for ongoing monitoring, fraud detection, financial crime, sanctions, and regulatory-risk platforms. Owns engineering strategy, shared decisioning capabilities, ML model lifecycle, agentic AI governance, platform scalability, and measurable risk and efficiency outcomes. The role manages distributed engineering, data science, and analytics teams while aligning risk, compliance, operations, payments, product, and technology stakeholders across multiple markets.

Lead and scale 24/7 security operations for MDR clients, managing SOC leaders, analysts, monitoring, threat detection, investigations, and incident response. Drive SOC process improvement, automation, AI-enabled capabilities, operational KPIs, SLAs, and service quality. Partner with security and customer-facing teams, serve as the senior escalation point for major incidents, and strengthen geographically distributed security operations.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

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.