Deployment Automation Jobs in Suffolk

2 of 2 Deployment Automation Jobs in Suffolk

Senior Platform Engineer

Ipswich, Suffolk, UK
Ntegra
Our Work - Ntegra The Platform Engineer will represent Ntegra, working directly with our high-profile public and private sector clients. Our Platform Engineers are responsible for the development and deployment of automation solutions using tools such as Ansible, Terraform and coding languages including Bash and PowerShell, as well as the management of cloud-based platforms, such as Azure … modernising legacy systems into cloud-native architectures to building and maintaining robust data platforms across multiple cloud providers. Implementation of secure data processing environments for classified information, create automated deployment pipelines for data applications and ML models, and design comprehensive multi-cloud solutions with robust monitoring systems. Leading technical transformation initiatives, working closely with data engineering teams to support … Implementation of security best practice and government security standards. Wider Responsibilities: Client-facing project work in the private and public sectors. (Requirement for UK Government Security Clearance.) Development and deployment of automated solutions using IAC tooling to automate the provisioning, configuration and deployment of IT infrastructure. Management of cloud-based platforms, such as AWS, Azure, and less often More ❯
Employment Type: Full-time
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Machine Learning Operations (ML Ops) Engineer

Ipswich, England, United Kingdom
Northampton Business Directory
into Production-ready software according to agreed performance and cost criteria. You’ll play a key role ensuring that ML/AI projects are setup for success via the automation of residual manual steps in the development and production lifecycle. You’ll also provide essential insights into the ongoing predictive capability and cost of deployed ML/AI assets … following categories: a) experiment tracking and model metadata management (e.g. MLflow) b) orchestration of ML workflows (e.g. Metaflow) c) data and pipeline versioning (e.g. Data Version Control) d) model deployment, serving and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering More ❯
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