AI Fine Tuning Expert

As an AI Fine Tuning Expert, your role will involve fine-tuning LLaMA models on domain-specific data such as finance, healthcare, telecom, legal, etc. You will be responsible for curating, cleaning, and pre-processing datasets for supervised and unsupervised fine-tuning. Additionally, your tasks will include implementing low-rank adaptation (LoRA), PEFT, QLoRA, or full fine-tuning as per the requirement. It will be crucial for you to optimize model training performance using various tools and libraries, and evaluate fine-tuned models using appropriate metrics. Furthermore, you will be expected to deploy and integrate models with APIs, RAG pipelines, or inference servers, and utilize tools like Weights & Biases, LangSmith, or TensorBoard for training monitoring and logging. Conducting safety audits and hallucination checks post-fine-tuning will also be part of your responsibilities. Familiarity with open-source LLMs beyond LLaMA (Mistral, Falcon, Mixtral, etc.), hands-on experience with orchestration tools like LangChain, LangGraph, CrewAI, or Flowise, knowledge of tokenizers, embeddings, and prompt templates, as well as proficiency in Python, PyTorch, and model training workflows are essential qualifications for this role. What we are looking for: - Deep expertise in Fine tuning in LLama, LoRA, QLoRA - Strong command of Python & ML Libraries In addition to the technical qualifications required for this role, it is important to note that you will have the opportunity to work with top-tier AI minds, gain access to high-performance infrastructure for model training, drive innovation with real-world applications, be part of a growing AI team building next-gen tools, experience nonstop learning and innovation, and benefit from competitive salary and growth opportunities. (Note: No additional details about the company were provided in the job description.),