18 of 18 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 ...

extraction, mapping, and transformation across heterogeneous data sources (IoT sensors, BMS systems, APIs, CSVs, PDFs, and more). Develop and refine ML models for anomaly detection, forecasting, and optimisation of building performance. Apply modern AI techniques — including LLMs, embeddings, and agentic workflows — to streamline data onboarding, metadata … agent frameworks. Experience working with real world, messy datasets and transforming them into structured, usable formats. Understanding of ML fundamentals, especially time series modelling, anomaly detection and AI ethics Ability to communicate insights clearly and collaborate across teams. A builder’s mindset — you enjoy prototyping, iterating ...

unstructured commercial and operational shipping data such as customs filings, fixtures, and SPAs. These inputs drive predictive systems that support energy‐demand forecasting, anomaly detection, and real‐time recommendations for physical and derivative trading. As a Principal Data Scientist, you will become a key part of Data … translating advanced research concepts into practical, high‐impact industrial applications, Fluent in Python and experienced in regression and classification modelling, clustering, time‐series analysis, anomaly detection, sequence‐to‐sequence architectures, and stochastic optimisation, Experienced across the full ML lifecycle: experiment design, model development, validation, deployment, monitoring ...

what you build from design through to deployment and iteration. What You'll Be Doing Designing and building AI agent systems for threat detection, behavioural correlation, sensitive data classification, and automated security response Developing and fine-tuning LLMs and ML models that run reliably in production Building … doing and why, to engineers and non-technical stakeholders alike Bonus if you have worked in cybersecurity domains (DLP, PII detection, anomaly detection), have built multi-step reasoning systems, or have spent time directly with customers understanding a problem domain. Why Apply? The category ...

components that improve performance and reliability across cloud-based distributed systems.* Analyze large-scale cybersecurity datasets to identify opportunities for improved classification, detection, and automation.* Translate ML/AI outcomes into actionable product decisions and collaborate closely with other Stakeholders internally and externally.* Establish and promote best practices … structure to ambiguous problem spaces and drive them toward actionable, high-impact outcomes.**Preferred:*** Experience with advanced ML techniques such as deep learning, GNNs, anomaly detection, or probabilistic modeling.* Experience defining or influencing ML/AI practices and strategies across the business, particularly for Principal-level candidates. ...

metrics Documenting assumptions and ensuring outputs are reproducible Developing scalable data workflows in SQL + Python (ingestion, cleaning, transformation, QA) Improving data quality: reconciliation, anomaly detection, root-cause analysis, and automated checks Building and maintaining dashboards for multiple stakeholders, ensuring data is accurate, timely, and clearly presented ...

running experiments, and deploying scalable solutions using modern cloud and MLOps tooling. Key Responsibilities Include: Designing and developing machine learning models (e.g. classification, forecasting, anomaly detection) Supporting experimentation cycles: hypothesis definition, testing, and evaluation Contributing to the deployment of models into production environments Building and maintaining ...

clients to scope, design, and deliver operationally-ready AI and ML solutions Key Responsibilities: Design, develop, and deploy machine learning models for forecasting, classification, anomaly detection, and LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly Transition validated experiments into production-ready ...

data Deep Learning NLP + LLMs, GenAI agent pipelines Simulations Graph-based models Time-series forecasting Geospatial modeling Causal inference Reinforcement learning Optimization problems Anomaly detection* **Deployment Experience*** Proven track record of deploying or partnering on **customer-facing production ML systems**.* Proficiency in Python ...

engineering stakeholders. Nice to Have: Experience within financial data pipelines, index calculation, or capital markets systems. Exposure to AI/ML-based tools for anomaly detection and automated troubleshooting. Experience monitoring application-layer and UI behaviour, beyond infrastructure metrics. Experience building SRE practices in a greenfield ...

error conditions, cost metrics, user behaviour signals, and system reliability.user experience optimisation**Key Responsibilities & Accountabilities** Own requirements for dashboards, monitoring tools, model comparison views, anomaly detection alerts, and performance scorecards.Partner with AI Evaluation PM (previous role), Model Risk, GSSR, Legal and Compliance to align telemetry with governance ...

Embed Zero Trust and least privilege principles across enterprise systems and privileged roles. Develop and automate identity governance processes, leveraging AI/ML for anomaly detection and remediation. Oversee Conditional Access, risk-based authentication, and device/state-based access controls. Integrate IAM with ...

audio software Work with generative AI tools and contribute to prompt engineering for intelligent media processing Collaborate with experienced engineers to design systems for anomaly detection, audio transcription, and event-based alerts Shape early-stage infrastructure for analysing and streaming audio/video data at scale Optimise ...

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 Transition validated experiments into production-ready solutions, working ...

whitepapers , contributing to product strategy Familiarity with security audits , RFP/RFI responses Exposure to security analytics tools and techniques, such as log analysis, anomaly detection, or traffic monitoring , with an interest in developing stronger skills. Understanding of full packet capture and analysis concepts, or hands ...

alerting workflows. Experience with streaming telemetry, including tools and protocols such as gNMI, gRPC, Telegraf or gNMIc. Exposure to AI or ML-driven monitoring, anomaly detection or predictive fault identification. Strong networking fundamentals across TCP/IP, BGP, OSPF, VLANs and optical networks. Comfortable working independently ...

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 Transition validated experiments into production-ready solutions, working ...

Monitor and evaluate emerging IAM trends (e.g., passwordless authentication, decentralised identity, adaptive access controls). - Lead automation and governance initiatives, including machine-learning-based anomaly detection. - Integrate and optimise multi-factor authentication, biometrics, and mobile identity capabilities. - Drive adoption of identity threat detection and response (ITDR) solutions. ...