Top Machine Learning Jobs in Edinburgh

Lead the creation of user-centric digital products in financial services, focusing on intuitive design and leveraging AI for enhanced user experiences.

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.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

As a Product Manager at Bringg, you will define product strategy, work with stakeholders, manage the roadmap, and integrate AI into logistics solutions.

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.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead and manage an ML engineering team building post-origination credit models for repayment, collections, recovery, and loss mitigation. Define technical strategy, design and scale ML solutions, partner with product, engineering and risk, mentor engineers, and operationalize models to minimize loan loss and personalize collections.

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.

Build and maintain short-term price-forecasting models for European power markets (day-ahead, intraday, balancing). Apply mathematical optimization and machine learning, integrate large market and weather datasets, design data pipelines, visualize results with Power BI, monitor policy impacts, collaborate with internal experts, and present client-facing insights.

Design and implement large-scale AI/ML systems using LLMs and RAG. Develop data pipelines, optimize models, and collaborate with teams on actionable intelligence solutions.

Design and build data-intensive backend services and APIs to manage large medical imaging datasets. Collaborate with product, frontend, and research teams to architect, test, and deploy performant solutions, mentor engineers, conduct code reviews, and prioritize solutions based on cost, value, and clinical needs.

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.

Lead and scale quantitative trading and liquidity strategies for NEAR Intents. Design game-theoretic models, build signal generation and execution systems, develop research and simulation infrastructure, translate research into production, monitor performance, and hire and mentor a quantitative research team while partnering with protocol and product teams.

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.