Machine Learning Ops Engineer

Thunes is seeking a Machine Learning Ops Engineer to bridge the gap between Data Science, AI Engineering, and Production Infrastructure. The successful candidate will architect and orchestrate a seamless multi-cloud environment, manage the AI tech stack, and ensure excellence in the MLOps lifecycle.

Requirements

• 5+ years of technical experience with a proven track record of shipping ML pipelines in production
• Multi-Cloud Fluency: Deep expertise in architecting solutions on major cloud platforms (e.g. AWS, GCP)
• Experience in LLM Observability & Cost Optimisation: Experience setting up stacks with self-hosted tools (e.g. Langfuse, LangSmith, Phoenix)
• Certifications: Google Professional Machine Learning Engineer or AWS Certified Machine Learning - Specialty / DevOps Engineer - Professional certification
• Holding a Bachelor’s degree in Computer Science, Engineering, or related fields
• Expert in Infrastructure as Code (IaC): Mastery of IaC (e.g. Terraform, OpenTofu)
• Proficient in DataOps: Proven implementation of Medallion Architecture on a Data Lakehouse
• Mastery of CI/CD & Automation: Advanced configuration of GitLab CI (e.g. Runners, Secrets Management)
• Proficient in Containerisation: Mastery of Docker, Kubernetes and orchestration (e.g. VM, K8s)