26 to 39 of 39 Anomaly Detection Jobs in the UK excluding London

other SOCs and cybersecurity researchers to identify analytics, threat intelligence, and tradecraft that benefit the Blue Team. Communicate funding and prioritization suggestions and lead implementation when needed. Develop complex, anomaly-based KQL analytics and playbooks for detection in M365, Linux, and Windows environments. Review open-source research on threats affecting cloud services and VMs, prioritizing and implementing … relevant findings. Research vulnerabilities, produce proof-of-concept exploits, and emulate adversary TTPs for training and detection evaluation. Review red team and pentest findings to improve detection rules. Provide forensic support and threat emulation to improve alert triage and accuracy. Identify gaps in SOC processes, data collection, and analysis, demonstrating the need for improvements through scenarios … AWS knowledge preferred. Understanding of Windows Active Directory and Windows OS fundamentals. Networking fundamentals experience. Experience with CI/CD and source control systems. Experience in developing malware and anomaly detections. Use of statistical methods for anomaly detection. Proficiency with Microsoft Sentinel and/or XDR. Strong skills in writing complex KQL analytics/searches. Awareness of current More ❯

network security technology related to Palo Alto Firewalls, Network access control (NAC), Proxy solutions, Remote Access and Extranet Third-Party Access solutions, intrusion Detection/Prevention, Network Anomaly Detection/Response, DNS security, Cloud Security and other network security technologies. The candidate must understand how the design of these security capabilities impacts management and administration More ❯

analysis, or EA, with 5+ years in finance systems. Proven expertise with finance operating models and KPIs (EBITDA, NPV, DSO). Experience with AI/ML in finance (e.g., anomaly detection, predictive AR). Skills & Tools Deep knowledge of SaaS, PaaS, microservices, data analytics, and EA frameworks. Familiarity with IT governance, DevOps, agile methodologies, and financial modeling. More ❯

health. Dashboard Development: Assist teams in creating clear, informative, and actionable dashboards to improve system visibility. Automation & Alerting: Automate monitoring and alerting processes, including enrichment strategies and ML-driven anomaly detection where applicable. Cross-Team Collaboration: Work closely with ICO and product development teams to ensure seamless visibility into system and service performance. Strategic Observability: Partner with More ❯

environments. You will work closely with experts in quantum sensing to develop quantum magnetometry technology that will solve pressing challenges in aeronautical positioning and navigation, geophysical surveying, and magnetic anomaly detection. A key focus of the role will be to develop novel software-layer control protocols and operating modes for optically-pumped atomic magnetometers that deliver step-change performance … pumped magnetometry in warm atomic vapour cells; quantum atomic physical systems; atom interferometry; pulse-level optimisation and quantum control techniques, digital signal processing (e.g. adaptive filtering, phase-sensitive detection). Ability to clearly communicate complex scientific ideas to a multidisciplinary team. Finally, you will have a strong desire to work with a world leading team and a company More ❯

environments. You will work closely with experts in quantum sensing to develop quantum magnetometry technology that will solve pressing challenges in aeronautical positioning and navigation, geophysical surveying, and magnetic anomaly detection. A key focus of the role will be to perform numerical modelling of optically-pumped atomic magnetometers, as well as related signal processing tasks, aimed at improving magnetometer More ❯

with a strong focus on performance, explainability, and cost-efficiency. What You'll Bring: Deep applied experience in ML/DL , with bonus points for work in threat detection , phishing , or abuse detection Proven ability to design and deploy full-stack AI pipelines in production Strong … experience in backend engineering , ideally with Go and ML frameworks like PyTorch or TensorFlow Familiarity with MLOps , cloud infrastructure (AWS) , Kubernetes , and Terraform Experience evaluating and deploying models (including anomaly detection, RAG, and clustering) in noisy, evolving data environments Nice to Have: Experience with Perl Knowledge of threat intelligence integration and MCP architectures Location: Hybrid - 2 days More ❯

transparency FinOps Tools Deployment - Manage cloud governance and FinOps tools to improve cost visibility and control Forecasting & Budgeting - Produce accurate cost projections and align cloud spend with financial planning Anomaly Detection - Identify and respond to cost anomalies to prevent unexpected budget spikes Reporting & Documentation - Prepare clear and comprehensive reports on cloud financial performance and optimisation measures Education More ❯

transparency FinOps Tools Deployment – Manage cloud governance and FinOps tools to improve cost visibility and control Forecasting & Budgeting – Produce accurate cost projections and align cloud spend with financial planning Anomaly Detection – Identify and respond to cost anomalies to prevent unexpected budget spikes Reporting & Documentation – Prepare clear and comprehensive reports on cloud financial performance and optimisation measures Education More ❯

or more organisational environments such as enterprise, edge/deployed environments or cloud . Demonstrable knowledge of cyber detection (e.g., threat identification/intelligence, real-time monitoring, anomaly detection) and cyber response (e.g. incident response, eradication and remediation, recovery, post-incident analysis). DevSecOps. Zero Trust Architecture (ZTA) expertise for enterprise, cloud and air-gapped More ❯

driven mindset. Hands-on approach , especially in the initial stages of project deployment . Experience with AI Tools for Infrastructure Management, leveraging AI-powered tools for AIOps , predictive maintenance , anomaly detection , and automated incident response . #J-18808-Ljbffr More ❯

world deployment. Key Skills & Experience Proficiency in Python and PyTorch for model development. Experience working with image-based machine learning models, including optical, UV, and thermal imaging. Understanding of anomaly detection, predictive maintenance, and synthetic data generation. Experience with high-voltage equipment is a plus. How to Apply To learn more, apply now or send your CV More ❯

as: Python for data science and ML Computer Vision, including OpenCV Model training, evaluation – accuracy, precision, recall, F1, dataset management Object detection, image classification, segmentation, depth estimation, anomaly detection Docker/containerisation. Personal Qualities and Experience You are someone who enjoys learning new skills, finding out things and also learning from mistakes. We’d like … in software , but you should be able to demonstrate your interest by having done something or worked on a ‘passion project’ yourself. You might have developed an object detection model, or built and trained an image classifier, or used OpenCV or similar to detect specific objects from a real-time feed, or some other relevant activity. You should More ❯

is designed, developed, tested, and maintained. This unit will explore the integration of AI tools and techniques—such as large language models, code generation systems, automated testing frameworks, and anomaly detection algorithms—throughout the entire SDLC. The goal is to increase development speed, improve code quality, reduce human error, and enable predictive maintenance. Key use cases, to … be prioritized during the project, also based on the industry needs, include AI-assisted coding, intelligent requirement analysis, automated bug detection and resolution, continuous integration optimization, and AI-driven documentation. Each unit will be at the frontier between fundamental AI methodologies and their rapid, scalable deployment in industrial environments. The goal: create high-impact, market-ready solutions while More ❯