MLOps Engineer

<h3>About Alta Ares</h3><p style="min-height:1.5em"><br />Alta Ares is an air defense Neoprime. We build AI-guided interceptors to counter drones and cruise missiles, along with the software platform that powers them.</p><p style="min-height:1.5em">Our customers are NATO-aligned militaries and defense institutions, and our systems are regularly deployed during live exercises and operational demonstrations across Europe, the Middle East, and Asia.</p><p style="min-height:1.5em">Founded in 2024, we have grown to 90 people, raised over $60M, and increased revenue 40× this year. We are now entering a new phase of international expansion, industrial scaling, fundraising, and product development.</p><p style="min-height:1.5em"></p><h1>Role &amp; Mission</h1><p style="min-height:1.5em">As an <strong>MLOps Engineer</strong>, you will own the evolution of <strong>Gamma Ulixes</strong>, the AI product platform powering both our internal development workflows and customer-facing AI capabilities.</p><p style="min-height:1.5em">You will work alongside Machine Learning Engineers, Software Engineers and DevOps Engineers to transform research prototypes into production-ready AI systems.</p><p style="min-height:1.5em">Beyond infrastructure, you will help shape the tooling, services and workflows that accelerate the entire machine learning lifecycle, from data ingestion to deployment on operational platforms.</p><p style="min-height:1.5em">This role is ideal for engineers who enjoy building products, automating complex workflows and enabling AI systems to scale reliably.</p><p style="min-height:1.5em"></p><h1>Your Responsibilities</h1><h2>Gamma Ulixes AI Platform</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Develop and improve Gamma Ulixes, our AI platform for training, evaluating and deploying machine learning models.</p></li><li><p style="min-height:1.5em">Build experiment tracking, model registry and dataset management capabilities.</p></li><li><p style="min-height:1.5em">Design reproducible ML workflows and automated training pipelines.</p></li><li><p style="min-height:1.5em">Develop benchmarking, evaluation and model validation services.</p></li></ul><p style="min-height:1.5em"></p><h2>ML Infrastructure</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Design scalable infrastructure supporting computer vision and trajectory-based machine learning.</p></li><li><p style="min-height:1.5em">Build APIs and backend services powering AI workflows.</p></li><li><p style="min-height:1.5em">Manage GPU infrastructure, distributed training and resource orchestration.</p></li><li><p style="min-height:1.5em">Improve monitoring, observability and reliability across AI services.</p></li><li><p style="min-height:1.5em">Maintain reproducible development and deployment environments.</p></li></ul><p style="min-height:1.5em"></p><h2>Deployment &amp; Edge AI</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Build CI/CD pipelines for machine learning models.</p></li><li><p style="min-height:1.5em">Deploy AI services across cloud, on-premise and edge environments.</p></li><li><p style="min-height:1.5em">Optimize inference