12 of 12 Permanent Anomaly Detection Jobs in London

using MLOps frameworks. Establish and enforce data governance policies, stewardship models, and metadata management practices Monitor and improve data quality using rule-based profiling, anomaly detection, and GenAI-powered automation Support GenAI initiatives through data readiness, synthetic data generation, and prompt engineering. Mandatory Skills: Cloud Platforms:Deep … Experience in defining semantic layers, asset hierarchies, and contextual models. Data Governance:Hands-on experience Data Quality:Ability to implement profiling, cleansing, standardization, and anomaly detection frameworks. Security & Compliance:Knowledge of data privacy, access control, and secure data exchange protocols. Defining and creating MLOPs pipeline Good ...

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 ...

manager on a key leadership hire - an Engineering Lead to spearhead the design, development, and modernization of cutting-edge transaction monitoring and fraud detection systems. This is a rare opportunity to lead a high-performing team and shape the future of fraud prevention and financial crime technology within … React.js for full-stack development Solid grasp of distributed systems design, secure coding, and data privacy principles. Familiarity with fraud detection models, anomaly detection, and rule-based systems. Experience with modern DevOps practices (CI/CD, Terraform, CloudFormation). If you have the skills ...

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 ...

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 ...

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 ...

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 ...