1 to 25 of 31 High Availability Jobs in the East of England

ingestion, enrichment and schema standardisation. Develop and tune security detection content, translating threat intelligence and TTPs aligned to MITRE ATT&CK into actionable, high-value alerts. Manage the full detection content lifecycle: design, test, deploy, monitor, tune and retire, using version control and rollback processes. Automate workflows and platform …/CD, SOAR, scripting and Infrastructure as Code tools such as Terraform and Ansible. Ensure platform performance, stability and resilience through capacity planning, high availability, disaster recovery and proactive monitoring. Provide technical leadership and guidance to internal teams and clients on security monitoring strategy and best practice. What ...

000pa Bedford, Hybrid Permanent, Full Time Can you Design, implement, and maintain robust, secure, and scalable network infrastructure solutions? Are you able to ensure high availability, performance, and security of bpha's network systems while mentoring junior staff and collaborating across IT teams? Then we want to hear … standards. Implement and manage network security measures (firewalls, VPNs, IDS/IPS). Configure and maintain routers, switches, wireless systems, and firewalls. Deploy scalable, high-performance network solutions with minimal downtime. Conduct regular network maintenance, updates, and upgrades. Perform security audits and vulnerability assessments. Respond to and mitigate network ...

lead everything that keeps Riverlane's technology estate running — from corporate IT operations to the development and management of our on‐premises high‐performance computing (HPC) infrastructure. This is a senior, hands‐on leadership role that sits at the intersection of enterprise IT and deep technical infrastructure, making … networking. Lead IT procurement, vendor management, and licence optimisation across all tools and platforms. Ensure robust IT support processes are in place, maintaining high availability and responsiveness for a technically demanding workforce of scientists and engineers. Own and develop Riverlane's information security posture, including policies, risk management ...

EBIs training mission. The role requires strong technical leadership, stakeholder management, and a holistic view of platform operations to ensure efficiency, cost control, and high service quality across all environments. In addition, the Platform Coordinator will lead the Solutions Architecture function, driving the standardisation of platform and solution architectures … plans for the platform team. Oversee the lifecycle of technical projects, ensuring timely delivery and adherence to best practices. Manage operational performance and ensure high availability of both on-premises and cloud platforms. Maintain and develop strong collaborative relationships with IT teams and EMBL-EBI service stakeholders. Lead ...

Upgrades & Patching System Administration (SAP Basis) System Copies & Client Administration system monitoring Transport Management System (TMS) User & Role Administration Nice To Have Automation & Scripting High Availability & DR Performance Tuning SAP on Cloud (Azure) SAP Security Audits Solution Manager (SolMan) Upgrade & Migration Support ...

Clearance due to the nature of some projects Responsibilities for Sys Admin: Set up, manage, and maintain Linux server environments, ensuring optimal performance and high availability. Apply security best practices across all systems, performing regular audits and updates. Support devices on Windows and macOS, ensuring smooth integration and functionality. ...

ability to operate effectively within an agile, service-oriented team. This role involves contributing to platform stability, implementing continuous improvements, and ensuring reliable, high-quality support for enterprise-scale Azure infrastructure while collaborating closely with senior team members and stakeholders. The Responsibilities Perform root cause analysis, investigation, diagnosis … reporting of cloud-related issues. Monitor and optimize Azure environments to ensure high availability, performance, and security. Troubleshoot and resolve build, deployment, and infrastructure issues. Ensure compliance with industry standards and best practices for security, scalability, and reliability. Create and maintain detailed documentation for processes, configurations, and procedures. ...

detection engineering Experience with automation, scripting or Infrastructure as Code in SIEM environments Understanding of MITRE ATT&CK and threat detection techniques Experience with high availability, disaster recovery and SIEM performance optimisation TO BE CONSIDERED Please either apply through this advert or email me directly at robin.muirhead@searchability.com ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

incident resolution Manage SAP installations, configurations, upgrades, Kernel patching, and system refreshes Support transport management processes across SAP landscapes Implement and maintain backup, recovery, high availability, and disaster recovery solutions Monitor and optimise database and system performance Support upgrade and migration activities including SP/FP stacks ...

Network Engineer to be responsible for the design, implementation, management, and optimisation of customer network environments, with a strong focus on network security and high availability. The ideal candidate will bring hands-on experience with Palo Alto, Cisco, and WatchGuard technologies, and ideally have a strong understanding of networking ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...