DevOps / MLOps Engineer

Blackthorn.ai is looking for a DevOps / MLOps Engineer to join our engineering team and help us build, maintain, and improve reliable cloud infrastructure for AI/ML and software projects.

You will work closely with developers, ML engineers, and other technical team members to automate deployments, manage cloud infrastructure, improve system reliability, and ensure secure and observable production environments.

What you’ll do:

Design, maintain, and optimize cloud infrastructure, primarily in Google Cloud Platform (GCP)

Build and manage infrastructure using Terraform and reusable Infrastructure-as-Code modules

Develop, maintain, and improve CI/CD pipelines and deployment automation

Work with Kubernetes and Docker to deploy and manage containerized applications

Support infrastructure for ML/MLOps workloads and microservices

Manage and improve IAM, access control, and security practices

Set up and maintain monitoring, logging, and observability solutions

Troubleshoot infrastructure and deployment issues and help ensure high availability and reliability

Collaborate with development and ML teams on infrastructure and deployment requirements

Automate routine infrastructure and operational tasks using Python and Bash

Contribute to cloud architecture and infrastructure improvements across projects

Requirements:

2+ years of experience in DevOps, Cloud Engineering, MLOps, or a related role

Strong hands-on experience with Google Cloud Platform (GCP)

Solid experience with Terraform / Infrastructure as Code

Practical experience with Kubernetes and Docker

Strong understanding of CI/CD principles and experience with tools such as GitHub Actions, GitLab CI, or Jenkins

Experience with Linux administration and cloud networking fundamentals

Understanding of IAM, access control, and cloud security

Experience with monitoring and logging tools such as Prometheus, Grafana, or similar

Good scripting skills in Python and/or Bash

Experience working with production environments

Ability to troubleshoot problems independently and take ownership of infrastructure-related tasks

Good English communication skills

Nice to have:

Experience with MLOps and infrastructure for machine learning workloads

Experience with AWS and/or Azure

Google Cloud certifications, such as Professional Cloud DevOps Engineer or Associate Cloud Engineer

Experience with GitOps and deployment automation

Experience with security and runtime monitoring tools such as Falco

Experience with distributed systems and microservices

What we offer:

Work on AI/ML and software engineering projects

Remote-friendly environment

International team and English-speaking environment

Opportunity to work with modern cloud and infrastructure technologies

High level of ownership and autonomy

Professional growth and opportunities to expand your expertise in DevOps, Cloud, and MLOps