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Description
Job Overview: We are seeking a highly skilled and innovative AI Automation Expert to lead the design, development, and deployment of intelligent automation solutions using state-of-the-art AI technologies. The ideal candidate will have deep expertise in AI agents, transformers, and large language models (LLMs), with hands-on experience in both pre-training and fine-tuning models for real-world applications. Key Responsibilities: Design and develop AI agents capable of handling complex automation workflows with minimal human intervention. Integrate and customize transformer-based LLMs (e.g., GPT, BERT, LLaMA) into business processes and digital platforms. Implement pre-training and training pipelines using distributed computing frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face). Collaborate with Marketing and Data teams to deliver end-to-end AI automation solutions across departments. Optimize model performance and cost-efficiency for production-grade deployment . Monitor and continuously improve the performance, safety, and accuracy of AI models in real-time environments. Stay ahead of the curve on emerging trends in LLMs, AI agents, and generative AI tools. Qualifications: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related fields. 2+ years of hands-on experience in AI/ML, with a focus on NLP, transformers, and automation . Proficiency in Python and relevant AI libraries (e.g., PyTorch, TensorFlow, Scikit-learn). Experience with pre-training and fine-tuning LLMs , including data preprocessing, tokenization, and model evaluation. Understanding of AI agent frameworks such as AutoGPT, BabyAGI, or custom-built solutions. Strong problem-solving skills and the ability to translate business problems into AI-powered solutions. Preferred Skills: Experience with RAG (Retrieval-Augmented Generation) , knowledge graphs, or vector databases (e.g., FAISS, Pinecone). Familiarity with prompt engineering, context management, and multi-agent systems.  Exposure to AI ethics, model interpretability, and responsible AI practices. Show more Show less
