MLOps Job Market Trends

A set of practices focused on the maintenance and optimization of large language models in production environments. It ensures that language models operate efficiently, with reliable performance and minimal downtime.

Refers to the hardware and software systems that support the development, deployment, and operation of artificial intelligence applications.

Develops and implements AI models and algorithms to solve complex problems and improve decision-making processes. Essential for advancing automation and technology-driven solutions in various industries.

Trains machine learning models across multiple computing nodes simultaneously.

An open-source platform for deploying, managing, and scaling machine learning workflows on Kubernetes.

An open-source platform for managing the end-to-end machine learning lifecycle, including experimentation, reproducibility, and deployment.

Artificially generated data used to train AI models, often employed when real data is scarce or sensitive.

A professional responsible for deploying, managing, and optimizing machine learning models in production environments. Ensures seamless integration of ML models with the infrastructure and CI/CD pipelines.

Machine Learning Operations (MLops) involves the practices and tools used to deploy, monitor, and manage machine learning models in production.