1 to 25 of 141 Anomaly Detection Jobs in England

Staff Machine Learning Engineer, Anomaly Detection United Kingdom, London Why PlayStation? PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including … and unforgettable gaming experiences. As we continue to push the boundaries of technology, we are seeking a talented Staff Machine Learning Engineer specializing in Anomaly Detection to join our dynamic R&D team. We are on a mission to revolutionize our QA processes by developing cutting-edge … unique opportunity to contribute to a global effort in making our QA processes more efficient and effective. As a Staff Machine Learning Engineer in Anomaly Detection, you will be the technical lead in a research team focused on advancing our anomaly detection technology, driving More ❯

and unforgettable gaming experiences. As we continue to push the boundaries of technology, we are seeking a talented Staff Machine Learning Engineer specializing in Anomaly Detection to join our dynamic R&D team. We are on a mission to revolutionize our QA processes by developing cutting-edge … unique opportunity to contribute to a global effort in making our QA processes more efficient and effective. As a Staff Machine Learning Engineer in Anomaly Detection, you will be the technical lead in a research team focused on advancing our anomaly detection technology, driving … anomalies in game streams. Your expertise will help shape the future of gaming by ensuring high-quality player experiences. What you'll be doing: Anomaly Detection Development: Design, develop, and implement novel anomaly detection algorithms to automatically identify bugs and glitches in game streams. More ❯

involves leveraging Machine Learning (ML) and Artificial Intelligence (AI) to deliver advanced insights that proactively improve system health and reduce Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR). The ideal candidate will have deep expertise in observability, monitoring, distributed systems, and strategic platform development. … Key Responsibilities Platform Leadership: Architect, design, and implement a scalable Observability Platform supporting metrics, logs, traces, and events; integrate ML/AI solutions for anomaly detection and predictive insights; develop platform capabilities to ensure system reliability and performance; establish standards and best practices. Strategic Initiatives: Collaborate with … metrics, logs, traces) and tools such as Prometheus, Grafana, OpenTelemetry, Jaeger, Kibana, Elastic Stack. Hands-on experience integrating ML/AI models for insights, anomaly detection, and predictive analysis. Strong expertise in designing scalable distributed systems for high-throughput data processing. Proficiency in programming languages such as More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯

native ML workflows. You'll work closely with data engineers, backend developers, and product leaders to embed ML across core features - from forecasting and anomaly detection to optimization and automated decision-making. Key Responsibilities: * Design and build serverless ML pipelines using AWS tools (Lambda, SageMaker, Step Functions … Develop, deploy, and monitor models in production (e.g., cost forecasting, anomaly detection, usage classification) * Collaborate on data ingestion and transformation with Snowflake, DBT, Airflow, and other pipeline tools * Work alongside backend engineers building APIs that serve model predictions and insights * Implement model observability, drift detection More ❯