Top AI Jobs in Edinburgh

Lead global Account Executive enablement by designing and delivering training, coaching, certifications, and sales methodology programs. Improve opportunity progression, conversion rates, deal quality, forecast accuracy, and sales cycle efficiency. Partner with Sales Leadership, Product Marketing, GTM Strategy, Revenue Operations, and regional teams to align programs with business priorities. Drive adoption of AI-assisted selling workflows for research, discovery preparation, stakeholder mapping, deal strategy, and follow-up creation.

Drive pipeline and bookings growth through strategic Global Systems Integrator partnerships across Europe. Develop joint business plans, coordinate enterprise sales pursuits, generate demand, strengthen executive relationships, expand partner-led services and platform adoption, and monitor performance through business reporting. Collaborate with Sales, Marketing, Product, Services, Finance, and alliance teams to execute go-to-market initiatives and deliver measurable revenue outcomes.

The VP Field Marketing is responsible for leading marketing strategy and execution in Europe, focusing on demand generation, brand awareness, and pipeline development while collaborating cross-functionally and driving a data-driven culture.

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.

Build scalable, full-stack, AI-enabled products for BlackRock’s Aladdin investment compliance and analytics workflows. Lead technical design, implementation, testing, deployment, production support, and continuous improvement. Apply generative AI, semantic search, retrieval, intelligent assistants, and agentic workflows responsibly. Partner with product, engineering, compliance, and business stakeholders to translate complex requirements into deliverable solutions. Influence architecture, champion DevOps and SRE practices, mentor engineers, and promote quality, resilience, security, observability, and maintainability across a global organization.

Provides technical leadership for production AI and machine learning systems, including generative AI, intelligent agents, predictive models, and optimization. Establishes architecture, engineering standards, evaluation and observability practices, and reusable AI platforms. Partners across business, engineering, data, risk, and control teams to deploy and operate scalable systems while optimizing performance, reliability, security, and cost. Mentors engineers and influences technical strategy.

Leads flagship AI Labs initiatives from scoping and research through production deployment. Designs and evaluates AI agents and agentic workflows, guides production-grade architecture, establishes quality and safety measurement, and partners with business and engineering stakeholders. Manages and mentors 3–6 AI scientists while communicating technical outcomes to senior leaders and broader audiences.

Leads research and production development of generative AI and large language model systems for cybersecurity. Responsibilities include defining AI research strategy, developing novel reasoning and summarization approaches, selecting model architectures and deployment strategies, building large-scale production systems, mentoring scientists, establishing evaluation standards, and guiding cross-functional technical initiatives. The role also represents the company through publications, speaking engagements, and technical thought leadership.

Conducts research on AI-enabled turbulence computation by designing, training, and releasing large neural network models for embedding and predicting high-Reynolds-number turbulent flows. The role applies graph neural networks, transformers, and dynamical systems theory, collaborating with academic researchers, industrial partners, and a major technology company. The position is full-time, fixed-term for 36 months, and includes opportunities for industrial collaboration and career development.

Conduct research on AI risk, algorithmic assurance, and insurance. Develop mathematical, statistical, and computational methods to evaluate, price, monitor, and mitigate AI-related risks. Build reproducible code, simulations, benchmarks, and evaluation tools; publish findings; present at conferences and industry workshops; collaborate with academic and industry partners; and support workshops, reports, grant development, and stakeholder engagement.

Develop and implement policy for responsible innovation, digital firms, emerging technologies, and personal data use. The role involves researching complex regulatory issues, providing data protection advice, influencing senior stakeholders, coordinating cross-organisational projects, identifying emerging risks, supporting regulatory supervision, and building relationships with businesses, innovators, regulators, and other organisations. The postholder will also represent the ICO at meetings, workshops, conferences, and regulatory forums in the UK and internationally.

Lead Standard Life’s digital and CRM vision, strategy, roadmap, and product ownership practice. Drive connected, personalized customer journeys across digital, voice, messaging, adviser, employer, and colleague channels. Partner with business, data, engineering, risk, compliance, and strategic teams to deliver measurable customer, commercial, and operational outcomes. Champion customer data, personalization, next-best-action, journey orchestration, and AI-enabled engagement while influencing executives, boards, governance forums, and prospective clients.

As a Staff Backend Engineer at GitLab, you'll enhance backend infrastructure for CI, integrate AI features, and ensure reliability and performance in CI/CD workflows.

Lead application engineering for an AI email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI capabilities to product experiences, guide a senior engineering team, make architecture and reliability trade-offs, and establish observability, monitoring, testing, and operational excellence. Partner with ML leadership to ship scalable, maintainable, and high-performing AI-powered experiences.

Own the end-to-end product direction and quality of AI-powered systems. Define requirements, evaluation frameworks, quality bars, and feedback loops while balancing model quality, latency, cost, reliability, safety, and user experience. Partner deeply with ML, backend, and client engineers on system design and iteration, identify failure modes, and drive execution in a fast-moving zero-to-one environment.

Own end-to-end data science solutions, including problem framing, feature and data structure design, experimentation, model development, deployment, monitoring, validation, and retraining. Write robust production-quality Python and SQL, communicate findings to technical and non-technical stakeholders, follow data governance and responsible AI standards, mentor junior colleagues, and improve modelling and engineering practices.

Lead new business development for CounselLink across the UK, managing the full enterprise sales cycle from prospecting through contract execution. Build executive relationships within corporate legal departments, develop enterprise pipelines, deliver product demonstrations, lead RFP responses, negotiate agreements, forecast sales, and identify cross-sell opportunities. The role requires consultative SaaS selling experience, familiarity with legal technology and the UK legal market, and the ability to influence senior stakeholders in a remote, cross-functional environment.

Own procurement management information and insight delivery using Power BI, the Nationwide Data Lake, and modern analytics tools. Build and optimise dashboards, data models, reports, and advanced analytics that support decision-making, risk management, and process improvement. Lead strategic reporting workstreams, ensure data governance and quality, translate stakeholder requirements into actionable insights, and monitor emerging technologies including AI. The role also involves procurement lifecycle reporting, senior stakeholder engagement, knowledge management, and key initiative leadership.

Design, build, and operate cloud-native AI infrastructure and platform services to support model development, training, evaluation, and inference. Implement IaC and automation, enable ML/LLM production deployments within governed enterprise environments, build observability and monitoring, collaborate with security and cross-functional partners, and support on-call/operational duties.

Manage relationships with AI-native startups, scaleups, and labs across the UK. Understand customer goals, develop AI solution strategies, drive adoption and growth, coordinate technical and business resources, build customer references and case studies, identify emerging use cases, and represent NVIDIA at industry events. The role requires deep AI ecosystem knowledge, strategic planning, cross-functional communication, and understanding of NVIDIA’s software, server, and cloud stack.

Develops NVIDIA’s Financial Services business in the UK by managing strategic accounts, building customer and partner ecosystems, identifying market opportunities, and promoting technology-enabled solutions. The role creates business plans, cultivates lighthouse customers and AI software partners, develops use cases and case studies, supports community marketing, and represents NVIDIA at industry events. It requires strong account management, partnership development, communication, strategic analysis, and knowledge of financial services applications, software, servers, and cloud services.

Own the function’s AI transformation strategy, prioritize high-impact opportunities, map workflows, and drive measurable adoption. Build and manage AI agents using no-code and low-code tools, configure skills and MCP connections, evaluate agent performance, and iterate solutions. Lead change management, champion networks, cross-functional collaboration, intake processes, and alignment with Enterprise AI and executive stakeholders.

Lead field-facing AI security strategy for enterprise customers by designing secure LLM/RAG architectures, delivering demos and POVs, advising on data protection and unsanctioned AI usage, and scaling enablement and product feedback across sales, product, and engineering teams.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, UX, and reliability. Define offline and online evaluation frameworks, incorporate human feedback, guide prioritization, and ensure AI features are understandable, predictable, safe, and trusted by users.

Own the end-to-end product strategy and execution for AI agent systems. Define technical and behavioral requirements, evaluate model performance, guide trade-offs across quality, latency, cost, reliability, and user experience, and partner closely with ML, backend, and mobile engineers. Establish evaluation frameworks, prioritize roadmaps, drive rapid and safe delivery, and ensure AI features are predictable, trustworthy, and valuable to users.