Generative AI Engineer

Qualifications:

Required:

5+ years of experience in software engineering with a strong focus on NLP and machine learning applications.

Proven expertise in building and deploying large language models (LLMs) using frameworks like TensorFlow, PyTorch, or other relevant tools.

Preferred:

Experience with various LLM architectures (e.g., BERT, Transformer).

Strong understanding of natural language processing concepts.

Strong understanding of Advanced RAG techniques.

Experience with NLP libraries (e.g., spaCy, NLTK) and techniques for fine-tuning and integrating LLMs into different applications.

Skills:

Proficiency in programming language: Python.

Experience with LLM frameworks: Experience with at least one of the following: TensorFlow, PyTorch, Hugging Face Transformers, etc.

Strong understanding of machine learning algorithms: Experience with various machine learning algorithms and techniques is essential for effectively customizing and integrating LLMs.

Experience with deep learning: Understanding of neural networks, backpropagation, etc.

Excellent knowledge of NLP techniques: Specifically, mention experience with:

Natural Language Understanding (NLU) concepts like intent classification, entity recognition, and dialogue management.

Proficiency in using large language models for tasks such as text generation, summarization, translation, or question answering.

Experience with specific LLM architectures relevant to the field, e.g., Transformers, BERT, BART, etc.

Experience with data analysis: Strong understanding of how to analyze and interpret the output from LLM models is crucial.