Top Machine Learning Jobs in Edinburgh

Build and validate verification systems to identify high-quality expert participants. Define problems, generate hypotheses, run experiments, prototype ML/statistical solutions, and turn approaches into production-ready models while collaborating across teams.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

The Forward Deployed Software Engineer will customize AI solutions for enterprise customers, maintain technical ownership, and bridge between support and engineering.

Lead identification, development, and global deployment of AI and automation solutions to optimize forms and precedents content operations. Prioritize opportunities, collaborate with cross-functional teams, ensure governance and quality, integrate solutions, report outcomes to leadership, and drive continuous improvement and responsible AI practices.

As a Lead Data Scientist, you will set technical direction, ensure project delivery, manage client relationships, and mentor data scientists.

The Computer Vision Engineer will lead AI initiatives in the defense sector, delivering solutions and mentoring teams while driving technical strategy and capability development.

Lead end-to-end research applying advanced ML/DL (transformers, GNNs, RL, ensembles) to generate alpha across digital asset markets, build production-grade pipelines, prevent leakage/overfitting, analyze microstructure and on-chain data, and mentor junior researchers.

Lead and develop a team of ML specialists to deliver production ML systems for fraud and financial crime. Set priorities, ensure model lifecycle practices (development, deployment, monitoring, governance), partner with Product, Risk, Engineering and Data, and raise standards for performance, explainability, reproducibility and observability while building an inclusive high-performing team.

Transform operational data into actionable insights by building semantic models, reporting solutions and metrics (Power BI/Fabric, DAX, M, SQL). Ensure data quality, governance, access controls, troubleshooting, documentation, and stakeholder collaboration to enable self-service analytics.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Designs and deploys supervised machine learning classifiers using curated patent data, conducts desk research on technologies, scopes and defines client classifier taxonomies, supports customer meetings and data review, and delivers ad-hoc analysis and presentations as projects progress.

Own and grow the EMEA territory by building pipeline, managing full sales cycles, closing enterprise travel-tech deals, and developing partnerships with TMCs and travel providers. Represent the company at events, engage senior executives, and share market feedback with Product and Leadership to drive strategic outcomes.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

Lead platform product ownership bridging cloud and firmware strategy and execution. Manage and prioritize backlog, engage customers, collaborate with R&D, define releases, and drive agile delivery aligned with product leadership.

Own the Device Intelligence product roadmap for tier‑1 network service providers. Define PRDs, AI/LLM-assisted workflows, and technical requirements; lead discovery, backlog prioritization, and cross-functional delivery; engage strategic customers and support sales with competitive positioning.

The Principal Solutions Architect leads technical solution design, partners with hyperscalers, ensures architectural integrity, and drives customer engagement through compelling narratives and demos.

As a C++ Engineer, you will develop machine learning features, integrate models, maintain SDKs, and collaborate across teams for software performance and enhancements.

As Senior Product Manager, you'll lead the integration of global airline partners, optimize supply metrics, and enhance product specifications for seamless booking automation, focusing on AI solutions and API performance.

Lead and deliver statistical support for Phase II-III clinical trials embedded with a sponsor: design input, SAP/sample size, interim/final analyses, oversight of programmers/statisticians, regulatory submissions, and collaborate cross-functionally to ensure compliant, high-quality statistical deliverables. Apply advanced statistical methods and ML/DL for analytics and process automation.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The Data Scientist will analyze data, build and refine machine learning models, document technical designs, and collaborate with multidisciplinary teams to deliver AI solutions.

The role involves building infrastructure for training open source foundation models, with emphasis on autonomy and contributing in a dynamic team.