AI Research Engineering Skills Library

The most comprehensive open-source library of AI research engineering skills for AI agents

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81 Skills Powering AI Research in 2026

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| | | | |:---:|:---:|:---:| | Model Architecture (5) | Fine-Tuning (4) | Post-Training (8) | | Distributed Training (5) | Optimization (6) | Inference (4) | | Tokenization (2) | Data Processing (2) | Evaluation (3) | | Safety & Alignment (3) | Agents (4) | RAG (5) | | Multimodal (7) | Prompt Engineering (4) | MLOps (3) | | Observability (2) | Infrastructure (3) | Mech Interp (4) | | Emerging Techniques (6) | ML Paper Writing (1) | |

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Table of Contents

• Our Mission
• Path Towards AI Research Agent
• Available AI Research Engineering Skills
• Demo
• Skill Structure
• Roadmap
• Repository Structure
• Use Cases

Our Mission

We provide the layer of Engineering Ability that enable your coding agent to write and conduct AI research experiments, including preparing datasets, executing training pipelines, deploying models, and building your AI agents.

<p align="center"> <img src="docs/skills.png" alt="AI Research Agent System" width="50%"> <br> <em>System diagram of an AI research agent</em> </p>

Path Towards AI Research Agent

Modern AI research requires mastering dozens of specialized tools and frameworks. AI Researchers spend more time debugging infrastructure than testing hypotheses—slowing the pace of scientific discovery. We provide a comprehensive library of expert-level research engineering skills that enable AI agents to autonomously implement and execute different stages of AI research experiments—from data preparation and model training to evaluation and deployment.

• Specialized Expertise - Each skill provides deep, production-ready knowledge of a specific framework (Megatron-LM, vLLM, TRL, etc.)
• End-to-End Coverage - 81 skills spanning model architecture, tokenization, fine-tuning, mechanistic interpretability, data processing, post-training, distributed training, optimization, evaluation, inference, infrastructure, agents, RAG, multimodal, prompt engineering, MLOps, observability, emerging techniques, and ML paper writing
• Research-Grade Quality -...