8 of 8 Remote AWS CloudFormation Jobs in the West Midlands

deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure … as-code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to … . Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda More ❯

deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure … as-code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to … . Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda More ❯

deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure … as-code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to … . Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda More ❯

deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure … as-code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to … . Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda More ❯

deploy ML models, algorithms and agentic AI systems to address complex business challenges across a range of sectors Cloud & MLOps Management: Lead the implementation of ML solutions on AWS cloud (with heavy use of Amazon SageMaker and related AWS services). Develop and maintain end-to-end CI/CD pipelines for ML projects, using infrastructure … as-code tools like AWS CloudFormation and Terraform to automate model deployment and system setup Project Leadership: Oversee the ML lifecycle from data preparation to model training, validation, and deployment. Make high-level design decisions on model architecture and data pipelines. Mentor junior engineers and collaborate with data scientists, ML engineers, and Software Engineering teams to … . Solid understanding of ML algorithms, model evaluation techniques, and optimisation. Experience with NLP techniques, generative AI or financial data modelling is advantageous Cloud & DevOps: Proven experience with AWS cloud services relevant to data science – particularly Amazon SageMaker for model development and deployment. Familiarity with data storage and processing on AWS (S3, AWS Lambda More ❯

designing, and executing deployment of network infrastructure including routers, switches, firewalls, and wireless systems across multiple sites Designing and implementing Infrastructure as Code solutions using tools like Terraform, CloudFormation, or Ansible Collaborating with operations and engineering teams to improve network design, optimize performance, and reduce latency Automating deployment and monitor tasks using scripting and configuration management tools Analysing More ❯

Your day-to-day will consist of: Leading and enhancing the company's infrastructure and tooling strategy. Implementing and improving Infrastructure as Code (IaC) with Terraform Working across AWS services - particularly IAM, S3, EKS Managing containerisation and orchestration. Delivering robust monitoring and alerting solutions Contributing to and maintaining CI/CD pipelines Driving ISO 27000 implementation and supporting … initiatives Introducing and managing cybersecurity tools such as vulnerability scanners, endpoint protection, SIEM, and cloud security monitoring solutions Requirements: Extensive experience in a DevOps team lead role using AWS, (IAM, S3, EKS). Experience with IaC such as Terraform.. Cloud formation/CDK is desirable. Expert knowledge in containerisation and orchestration technologies such as Docker and Kubernetes. Proficiency More ❯

DevOps Engineer - Burton upon Trent/Hybrid Hybrid workingSalary up to £60,000 per annumA leading client in Burton seeks a DevOps Engineer to design, implement, and maintain AWS and Azure cloud infrastructure. The role involves supporting continuous integration and delivery, ensuring reliability and security, and sharing expertise to help develop the team. Key skills and responsibilities: Design … deploy, and manage secure, scalable AWS infrastructure. Build and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, or Jenkins. Set up monitoring, alerting, and logging with tools like Datadog, Logic Monitor, and Solarwinds. Strong grasp of DevOps principles; hands-on CI/CD experience. Microsoft Certified: DevOps Engineer Expert (AZ-400). Design and deploy containers … on AKS/EKS with CloudFormation or ARM templates. Automate tasks using PowerShell, Bash, or Python. Manage infrastructure with Terraform, Bicep, or ARM templates (HashiCorp Certified: Terraform Associate). Enforce security compliance and access controls (IAM, PIM, RBAC). Respond to incidents; conduct root cause analysis and post-mortems. Maintain documentation and runbooks. Collaborate cross-functionally to align More ❯