Natural Language Processing Job Market Trends

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LangGraph

100-200
Employers
+5325%
Growth

A tool or library for visualizing and managing language model workflows, enhancing understanding and optimization.

Agentic

400-800
Employers
+3046%
Growth

Agentic refers to AI systems or agents that possess the ability to act autonomously, making decisions and performing tasks without direct human intervention. These systems are designed to achieve specific goals by leveraging machine learning and decision-making algorithms.

Cursor AI

60-120
Employers
+1371%
Growth

An AI-powered code editor designed to enhance the productivity of software developers. It integrates advanced AI capabilities to assist with code completion, error detection, and refactoring, providing real-time suggestions and improvements as developers write code.

DSPy

20-40
Employers
+550%
Growth

DSPy is an open-source framework developed by Stanford NLP for programming language models, focusing on building modular AI systems rather than relying on traditional prompting.

Ollama

30-60
Employers
+320%
Growth

Ollama is an open-source framework designed for serving large language models (LLMs) locally on on-premise devices. It supports multiple operating systems, including macOS, Linux, and Windows, and offers flexible interaction modes through a Command Line Interface (CLI), SDK, or API.

AI Agent

600-1.2K
Employers
+314%
Growth

An autonomous entity that uses artificial intelligence to perform tasks, make decisions, and interact with environments or users.

Google Gemini

40-80
Employers
+310%
Growth

An AI platform by Google designed to enhance machine learning workflows and model training.

Small Language Model

15-30
Employers
+309%
Growth

A type of language model designed with fewer parameters and computation resources than large models. They can be used for lightweight applications and resource-constrained environments.

vLLM

70-140
Employers
+284%
Growth

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