ML Ops Engineer

Build and maintain reproducible training and evaluation pipelines, along with the templates and tooling modelers rely on. Implement CI to ensure ML runs are genuinely comparable across code, config, and models, while managing a model lifecycle registry from sandbox to production. Keep experiment results traceable and wire on-device and hardware-in-the-loop test runs into automation to collect results. Own the infrastructure machinery that frees modelers to focus on model development rather than setup. Operate out of Paris, Lausanne, or Zurich with 100% dedication to Harmattan AI's mission of providing a defensive edge to allied nations through ethical, high-impact technology.