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What You’ll Work On:

  • Fine-tuning pre-trained LLMs on small to medium datasets (500–20k examples)
  • Implementing parameter-efficient fine-tuning (e.g., LoRA-style methods)
  • Optimising training for cost and performance

Experience:

  • Strong Python skills
  • Experience with deep learning frameworks: PyTorch (preferred) or TensorFlow
  • Experience with Hugging Face Transformers or similar ecosystems

What You’ll Gain:

  • Real-world experience fine-tuning large models (30B–100B parameter class)
  • Exposure to production constraints and deployment
  • Opportunity to co-author technical writeups if applicable

TensorOps

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