MLOps Engineer, Protex AI

• 3–5+ years of experience in DevOps, MLOps, or ML engineering roles
• Experience automating ML workflows using CI/CD pipelines (e.g., Github actions, GitLab CI, Jenkins, AWS CodePipeline)
• Strong coding skills in Python and experience writing unit and integration tests for ML pipelines
• Hands-on experience with containerisation (Docker) and AWS infrastructure (ECS, S3, AWS Batch)
• Familiarity with infrastructure-as-code (e.g., Terraform or CloudFormation)
• Experience building observability systems for ML (metrics, logs, model performance tracking)
• Understanding of model versioning, reproducibility, and testing best practices
• Awareness of cloud cost optimisation practices (e.g., spot instances, autoscaling)
• Experience supporting a production ML environment and collaborating across cross-functional teams

Desirable

• As an MLOps Engineer, you’ll design, scale, and optimise our computer vision pipelines to serve thousands of clients.
• You’ll own the infrastructure that powers our ML models in production. Automating workflows, improving observability, and ensuring reliable, cost-efficient deployment at scale