MLOps Job Market Trends

A library designed for accelerated AI model inference utilizing advanced techniques for efficiency. It enhances large language models' performance on modern hardware architectures.

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

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.

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.

Designs and oversees the implementation of AI solutions, ensuring they meet business requirements and technical standards.

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

Trains machine learning models across multiple computing nodes simultaneously.

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

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.