MLOps Engineer
Experiment Tracking
Version control system for machine learning data, models, and pipelines.
Open-source platform for tracking experiments and managing the ML lifecycle.
Experiment tracking and model registry platform for ML teams.
Experiment tracking, dataset versioning, and model management platform.
Model Serving
Kubernetes-native platform for building and deploying ML workflows.
Open-source inference server for deploying models at scale across hardware.
Scalable model-serving library built on the Ray distributed compute framework.
High-throughput LLM inference/serving engine; the current standard for self-hosting open-weight LLMs at scale.
Managed ML Platforms
Fully managed AWS service for building, training, and deploying ML models.
Unified data and AI platform built around Apache Spark and the lakehouse.
Open-source feature store for operationalizing ML features in production.
Google Cloud's unified managed ML platform, its counterpart to SageMaker and Databricks.