Hermes Corporate
Website:
hermescorporate.it
Company:
https://www.linkedin.com/company/hermes-corporate
Seniority: Director
Industries: IT Services and IT Consulting, Oil and Gas, and Business Consulting and Services
Job details:
DevOps / MLOps Engineer | AWS | CI/CD | AI/ML Infrastructure
About the role
We are looking for a strong DevOps / MLOps Engineer to own and evolve the infrastructure, automation and deployment practices supporting AI/ML models and applications.
This role sits at the intersection of DevOps, cloud infrastructure and MLOps. The ideal candidate has deep hands-on experience building robust CI/CD systems, managing AWS infrastructure and taking machine learning models from development through controlled production deployment and monitoring.
What you'll do
- Assess, improve and extend existing CI/CD pipelines, increasing reliability, consistency and coverage
- Enhance automation frameworks and repository templates used to build, validate and deploy packages, applications and ML models
- Own controlled promotion across development and production environments, including approval gates and rollback strategies
- Manage cloud services underpinning the AI/ML and application estate, including:
- Identity and access architecture
- Federated authentication from source control
- Artifact and container registries
- Compute and model-serving infrastructure
- Maintain build infrastructure, including self-hosted runners with access to accelerated compute
- Own the ML model lifecycle, including:
- Model registry and versioning
- Packaging models for inference
- Promotion criteria
- Production deployment
- Monitoring of deployed models
- Define container image build standards and embed image scanning and vulnerability gates into CI/CD pipelines
- Maintain and improve Infrastructure as Code, ensuring environment configuration remains consistent and in parity
- Contribute to data management and governance standards supporting AI/ML readiness
What we're looking for
- Strong, hands-on DevOps and CI/CD experience
- Deep experience with source-control-native CI/CD tooling, particularly GitHub Actions or equivalent
- Experience designing reusable, modular and templated workflows
- Strong AWS experience, including:
- IAM
- Cross-account architecture
- OIDC federation
- ECR
- Container compute
- Serverless compute
- Strong Infrastructure as Code experience using Terraform or AWS CDK
- Proven MLOps experience across the full model lifecycle, from model registry through production serving and monitoring
- Experience building and maintaining containerized deployment pipelines
- Strong understanding of software supply-chain security, including container scanning and vulnerability gating
- Ability to work independently and take ownership of infrastructure end-to-end
Nice to have
- Experience connecting on-premises AI/ML training infrastructure with cloud-based model serving
- Experience supporting AI/ML platforms in a regulated or enterprise engineering environment
- Experience with cloud cost management and capacity governance
- Experience working with accelerated or GPU-based compute infrastructure
Click on Apply to know more.
