Azure - MLOps Engineer
Moative is seeking an experienced Azure MLOps Engineer to oversee the entire ML lifecycle on Azure, from proof-of-concept to large-scale production deployments. This role involves building and maintaining automated training, validation, and deployment pipelines, integrating MLOps practices, and collaborating with cross-functional teams to deliver robust ML solutions.
Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.
Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.
We seek experienced ML/AI professionals with strong backgrounds in computer science, software engineering, or related fields to join our Azure-focused MLOps team. If you’re passionate about deploying complex machine learning models in real-world settings, bridging the gap between research and production, and working on high-impact projects, this role is for you.
As an operations engineer, you’ll oversee the entire ML lifecycle on Azure—spanning initial proofs-of-concept to large-scale production deployments. You’ll build and maintain automated training, validation, and deployment pipelines using Azure DevOps, Azure ML, and related services, ensuring models are continuously monitored, optimized for performance, and cost-effective. By integrating MLOps practices such as MLflow and CI/CD, you’ll drive rapid iteration and experimentation. In close collaboration with senior ML engineers, data scientists, and domain experts, you’ll deliver robust, production-grade ML solutions that directly impact business outcomes.
Posted June 10, 2026