DevOps / MLOps Engineer
- Full-time
- Mid level
- Remote (worldwide)
Remote DevOps / MLOps Engineer at MacroCoderz: run cloud infrastructure, CI/CD and monitoring for production AI systems, LLM services and vector databases.
Role at a glance
| Employment type | Full-time |
|---|---|
| Level | Mid level |
| Experience | 3+ years |
| Location | Remote (worldwide) |
| Team | Software and infrastructure |
| Education | Degree in computer science or equivalent practical experience |
| Posted | 10 October 2026 |
About the role
AI systems bring infrastructure problems of their own: model endpoints with unpredictable latency, vector databases that grow fast, GPU workloads, and API bills that need watching. As a DevOps / MLOps Engineer you keep all of it reliable, secure and affordable.
You own environments across AWS, GCP and Azure, the pipelines that ship code and models, and the monitoring that tells us something is wrong before a client does.
What you will do
- Build and maintain CI/CD pipelines for application code, prompts and models.
- Provision cloud infrastructure as code.
- Run containers and services reliably in production.
- Set up monitoring, logging, alerting and LLM cost tracking.
- Apply security practices: secrets management, access control, backups and patching.
What we are looking for
- 3+ years running production workloads on AWS, GCP or Azure.
- Strong Linux, Docker and a CI/CD tool such as GitHub Actions or GitLab CI.
- Infrastructure as code with Terraform, Pulumi or similar.
- Scripting in Bash or Python.
Nice to have
- Kubernetes experience.
- Has deployed GPU workloads, model servers or vector databases.
- Observability tools such as Grafana, Prometheus or Datadog.
Skills and tools
- AWS
- GCP
- Azure
- Docker
- Kubernetes
- Terraform
- CI/CD
- Linux
- Monitoring
Who this role suits
DevOps, SRE and platform engineers who want to specialise in infrastructure for AI and machine learning.
The work behind this role
DevOps / MLOps Engineer: common questions
Yes. The DevOps / MLOps Engineer role at MacroCoderz is fully remote and open to applicants worldwide. It is a full-time, mid level position.
3+ years (mid level). Education: Degree in computer science or equivalent practical experience. Who it suits: DevOps, SRE and platform engineers who want to specialise in infrastructure for AI and machine learning.
DevOps covers building, deploying and running software reliably. MLOps applies the same discipline to machine learning: versioning models and prompts, deploying model endpoints, monitoring output quality and cost, and handling GPU and vector database workloads. This role covers both.
Use the application form on this page. It asks for your contact details, city, LinkedIn profile, expected salary, how you heard about the role, a short description of two or three projects you have worked on, and your CV as a PDF or Word file. An engineer reviews every application and emails shortlisted applicants to arrange a call.