Top Machine Learning Jobs in Edinburgh

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 technical direction for GitLab’s Core DevOps services, covering CI, CD, planning, and source control. Defines architecture, quality metrics, migration strategies, and technical roadmaps; addresses systemic risk and complex design decisions; prototypes and writes code when needed; partners with Infrastructure, Security, SRE, and Product; adopts AI capabilities; mentors senior engineers; supports incident response and senior technical hiring.

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.

Participate in a 12-month data science graduate programme, developing models and AI solutions across their full lifecycle. Apply statistical analysis, machine learning, data visualization, and cloud technologies to complex business problems. Collaborate with engineers, analysts, and cross-functional teams to generate actionable insights while developing expertise in responsible AI, data privacy, and customer-focused innovation.

Provide expert technical advice on age assurance and digital identity technologies within online safety regulation. Lead research and evaluations, assess technical feasibility and risks, translate complex concepts for policy and leadership audiences, prepare briefings and demonstrations, monitor emerging trends, and engage with academia, industry, public bodies, and external technical groups.

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.

The Director of FP&A will own budgeting, rolling forecasts, integrated financial modeling, cash flow and headcount planning, SaaS KPI reporting, variance analysis, board reporting, and PE sponsor reporting. The role will improve planning infrastructure across NetSuite, Salesforce, Pigment, and Bob, apply AI to finance workflows, and lead and develop the FP&A team across a multi-entity, multi-currency SaaS business.

Build scalable, low-latency backend APIs, event-driven services, integration layers, and microservices supporting personalization and recommendation experiences. Partner with AI/ML and data engineers to deploy models, expose AI services, and develop React applications. Improve security, observability, reliability, performance, scalability, and operational efficiency while using AI-assisted engineering tools to enhance delivery and code quality.

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

Manage the full sales cycle across EMEA, including prospecting, pipeline generation, client meetings, contract negotiation, and closing. Build strategic partnerships with mobile gaming and other app-focused clients, exceed revenue quotas, and collaborate with Customer Success, Marketing, and Product. Represent the company at industry events, track mobile advertising trends, and use AI technologies to improve prospecting and sales performance.

Manage NVIDIA’s relationships with cloud and technology partners, driving adoption of AI platforms and solutions. Develop partner strategies, quantify market opportunities, create value propositions, coordinate technical, business, and marketing resources, and cultivate customer references and emerging use cases. Lead ecosystem engagement across solution providers, integrators, startups, and enterprises, while supporting demand generation, community marketing, business development, and industry events.

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.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Conduct computational analyses of genomic, transcriptomic, proteomic, and other biomedical datasets to identify drug targets, biomarkers, and disease subtypes. Apply machine learning, deep learning, and omics methods; integrate multi-omics data; review literature; interpret results; design validation strategies; and develop visualizations and reports. Collaborate with AI, biology, chemistry, imaging, and medical experts while contributing to agentic AI systems and internal research methodologies.

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.

Lead regional field sales teams, develop sales strategies and account plans, manage pipeline and forecasts, recruit and coach sales managers, close enterprise technology deals, and grow business through customers, resellers, and partners. The role requires strong technical knowledge of cybersecurity, cloud, networking, and IT infrastructure solutions, executive-level selling skills, and the ability to manage remote teams across the NEMEA region.

Drive adoption of Rapsodo Golf solutions across UK golf ranges, clubs, and facilities. Responsibilities include prospecting, relationship building, on-site demonstrations, full-cycle sales, contract negotiation, installation coordination, post-installation support, CRM pipeline management, territory planning, event representation, and sharing customer and competitor insights with internal teams.

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.

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.