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.

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.

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.

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.

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.

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.

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 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.

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 independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

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.

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.