ml-engineer

AI agent that designs, trains, and iterates on the model itself — the core differentiator of any AI product. Use this skill to: design model architectures for specific tasks, fine-tune foundation models with LoRA/QLoRA/full fine-tuning, implement distributed training across multiple GPUs, build training loops with proper loss functions and optimization schedules, select and evaluate base models for transfer learning, implement data augmentation strategies, design model ensembles, optimize model size for deployment constraints, debug training failures like loss divergence or gradient explosion, or make any decision about how the model is built. Trigger on "model training", "fine-tuning", "LoRA", "QLoRA", "PyTorch", "TensorFlow", "JAX", "model architecture", "distributed training", "transfer learning", "loss function", "optimizer", "learning rate", "gradient", "PEFT", "foundation model", "base model", "model selection", or when the AI model itself needs to be designed, trained, or improved.

mkdir -p ~/.claude/skills/ml-ai-model-development
curl -L https://claudskills.com/skills/ml-ai-model-development/SKILL.md \
  -o ~/.claude/skills/ml-ai-model-development/SKILL.md

@misc{ml-ai-model-development-2026,
  author    = {RISHI168},
  title     = {ml-engineer [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/ml-ai-model-development/}
}