ML Engineer
2 articles in this category.
MLOps and LLMOps — Complete Production Architecture Guide
Introduction Modern AI systems are no longer just about training models. Today, companies need: This is where: become critical. Although they are related, they solve different problems. What is MLOps? MLOps (Machine Learning Operations) is the engineering discipline that manages the full lifecycle of traditional machine learning systems. It combines: MLOps focuses on: Typical use…
The New AI Stack — Roles, Responsibilities, and Tools
1. Infrastructure Layer Role: Provision, monitor, and manage the scalable infrastructure required for model deployment and data processing. Roles Involved: Responsibility Tools / Tech Roles Involved Compute Management SkyPilot, Kubernetes, Ray DevOps, MLOps Data Management Feast, LakeFS, Airbyte DataOps, MLOps Model Serving vLLM, Triton, TorchServe MLOps, DevOps Monitoring & Logging Prometheus, Grafana, Arize MLOps, DevOps…