16 of 16 Permanent Anomaly Detection Jobs in London

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What you will be doing: Push the frontier of research in areas such as deepfake detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation strategies ...

machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML. What y ou will be doing : Push the frontier of research in areas such as deepfake … detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML. Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products. Representative work: Implement bias-mitigation ...

while shaping a platform designed for reliability, scalability, and intelligence. In this role, you’ll: 🧠 Develop and optimise machine learning workflows, including predictive modelling, anomaly detection, and decision-making systems 🛠 Support the design and maintenance of cloud-based infrastructure (GCP, Azure, or AWS) 📡 Contribute to data pipelines … skills and experience with ML frameworks and tooling ☁️ Exposure to at least one major cloud platform (GCP, Azure, AWS) 📊 Understanding of ML workflows — especially anomaly detection, predictive modelling, and model evaluation 🔧 Familiarity with MLOps concepts such as deployment, monitoring, and reproducibility 🖥 Interest in multi-modal LLMs ...

while shaping a platform designed for reliability, scalability, and intelligence. In this role, you’ll: 🧠 Develop and optimise machine learning workflows, including predictive modelling, anomaly detection, and decision-making systems 🛠 Support the design and maintenance of cloud-based infrastructure (GCP, Azure, or AWS) 📡 Contribute to data pipelines … skills and experience with ML frameworks and tooling ☁️ Exposure to at least one major cloud platform (GCP, Azure, AWS) 📊 Understanding of ML workflows — especially anomaly detection, predictive modelling, and model evaluation 🔧 Familiarity with MLOps concepts such as deployment, monitoring, and reproducibility 🖥 Interest in multi-modal LLMs ...

chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards ...

focus on pricing and risk analytics Build scalable ML pipelines for processing large-scale financial data Develop deep learning architectures for time series prediction, anomaly detection, and pattern recognition in market data Optimize model performance through advanced techniques including hyperparameter tuning, ensemble methods, and neural architecture search ...

deploy production-grade ML and GenAI solutions in high-impact operational environments. What youll be doing: Design and build ML models across forecasting, classification, anomaly detection, and GenAI/LLM use cases Lead experimentation cycles: hypothesis, evaluation, iteration, and validation Take successful ML approaches into production, including ...

environment where you will apply cutting-edge machine learning methods to unique datasets. Key responsibilities: Lead and contribute to ML projects, including forecasting, classification, anomaly detection, and LLM/GenAI applications. Design experiments, formulate hypotheses, evaluate results, and iterate rapidly to validate approaches. Transition experimental models into ...

huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements ...

product management productivity (e.g., research, requirements drafting, data analysis, workflow automation). Interest in applying AI/ML to billing or financial systems (e.g., anomaly detection, collections optimization, LLM-powered support tools). Strong technical aptitude; able to dive into data models, APIs, and integrations to inform ...

product management productivity (e.g., research, requirements drafting, data analysis, workflow automation). Interest in applying AI/ML to billing or financial systems (e.g., anomaly detection, collections optimization, LLM-powered support tools). Strong technical aptitude; able to dive into data models, APIs, and integrations to inform ...

corrective and preventive action plans to reduce defect recurrence. Enhance application logging and observability standards across Guidewire services to improve MTTR , proactive alerting, and anomaly detection. Design, manage, and maintain centralized monitoring and observability dashboards for real-time application health tracking. Enforce Guidewire best practices, architectural standards, and SurePath ...

Monitoring Infrastructure : Build real-time systems that track agent behaviour across risk factors including agent-to-agent interactions, privilege escalation attempts, emergent capability detection, and behavioural drift from baseline parameters • Risk Assessment Engine : Design algorithms that quantify AI risk in financial terms (£X exposure), map behaviours to regulatory … Integration : Implement monitoring for agent communication protocols (Model Context Protocol, Agent2Agent, Agent Connect Protocol) as they mature, ensuring authenticated and logged inter-agent communications • Anomaly Detection : Develop ML systems that identify when agents exhibit unexpected strategies, attempt unauthorized actions, or drift from intended behaviour—catching issues before ...

Monitoring Infrastructure : Build real-time systems that track agent behaviour across risk factors including agent-to-agent interactions, privilege escalation attempts, emergent capability detection, and behavioural drift from baseline parameters • Risk Assessment Engine : Design algorithms that quantify AI risk in financial terms (£X exposure), map behaviours to regulatory … Integration : Implement monitoring for agent communication protocols (Model Context Protocol, Agent2Agent, Agent Connect Protocol) as they mature, ensuring authenticated and logged inter-agent communications • Anomaly Detection : Develop ML systems that identify when agents exhibit unexpected strategies, attempt unauthorized actions, or drift from intended behaviour—catching issues before ...