Take your career to new heights with Loopio! 🚀✨
We’re looking for a skilled and motivated MLOps Engineer to help scale and productionize the machine learning systems that power Loopio’s intelligent product features. In this role, you’ll work closely with ML Engineers, Data Scientists, and Backend Engineers to build the pipelines, infrastructure, and tooling needed to deliver high-impact ML models to our users; reliably, efficiently, and at scale.
You’ll be a critical part of enabling our AI/ML roadmap, from intelligent search and content suggestions to document automation and agent copilots, by ensuring models can be deployed, monitored, and continuously improved in production environments.
This is a great opportunity to grow your expertise in applied MLOps, contribute to high-leverage systems, and be part of a fast-moving, collaborative team working at the intersection of ML, engineering, and product.
What You’ll Be Doing
Pipeline & Workflow Development: Build and maintain robust ML pipelines for training, evaluation, and deployment. Automate routine workflows and support reproducible, auditable experimentation.
Model Deployment & Inference: Package and deploy models into production environments using tools like Docker, Kubernetes, and SageMaker. Build REST/gRPC services to serve models in real-time or batch.
Monitoring & Reliability: Help implement systems to monitor model health in production, detect drift, and log predictions. Contribute to alerting and dashboarding that helps the team maintain trust in deployed models.
CI/CD for ML: Work within our CI/CD systems to support model validation, promotion, and rollback. Help build safe, automated workflows for taking models from development to deployment.
Collaboration & Support: Partner with ML E...
