Top Machine Learning Jobs in Edinburgh

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.

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.

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.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Leads biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Research, design, and develop algorithms and software systems for AI-driven CNC machining, including toolpath optimization, cutting strategies, and automated CAM workflows. Collaborate with manufacturing experts, data scientists, and software engineers to convert advanced concepts into reliable production software. The role emphasizes high-performance C++ development, computational geometry, numerical methods, optimization, and modern software engineering practices.

Leads commercial performance for global and regional eCommerce markets, improving revenue, margin, EBIT, conversion, AOV, demand shaping, customer experience, and retention. Partners with market leaders to diagnose performance, recommend actions, align improvement plans, govern KPI frameworks, and ensure adoption. Leads data storytellers, establishes analytical and measurement standards, develops global playbooks, and influences senior stakeholders across a global matrix organization.

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 commercial growth execution as the CCO’s operating partner, translating strategy into measurable GTM programs across Sales, Marketing, Customer Success, Partnerships, and Operations. Owns growth orchestration, execution frameworks, KPI dashboards, performance reporting, enablement, accountability systems, and recurring commercial operating rhythms. Aligns cross-functional leadership, removes execution barriers, improves forecast confidence, and drives scalable growth initiatives across a life sciences SaaS organization.

Organize and maintain sales playbooks, battlecards, objection-handling guides, and competitive content. Design onboarding and ramp programs, deliver ongoing sales coaching, identify training gaps, and coordinate content development with instructional designers. Manage enablement content and adoption within Docebo, using usage data to improve effectiveness. Partner cross-functionally with Sales, Marketing, and Product in a B2B SaaS environment.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

Leads positioning, messaging, go-to-market strategy, launches, sales and channel enablement for Sophos AI cybersecurity solutions. Develops category narratives, launch assets, competitive intelligence, analyst relationships, customer feedback programs, and partner enablement. Collaborates cross-functionally with product management, research, sales, marketing, and channel teams to translate technical capabilities into differentiated market stories and pipeline outcomes.

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.

Develop and evaluate machine learning models for customer feedback, including classification, extraction, summarization, sentiment analysis, retrieval, reranking, and semantic search. Build LLM-powered features, evaluation frameworks, fine-tuning pipelines, and model integrations. Collaborate with Data Science, Engineering, and Product teams to translate requirements into experiments and production solutions, while monitoring research and documenting work clearly.

Owns ActAI’s global technical recruiting function, including hiring strategy, senior engineering and AI searches, recruiting team leadership, talent assessment standards, executive partnership, and scalable recruiting processes across the US, Europe, and Asia. The role combines hands-on headhunting with building and coaching a high-performing technical recruiting organization.

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.

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.