Experience: professional experience in data science, machine learning, and AI, with specific experience in NLP, LLMs, and GenAI applications.
- Education: Bachelors or masters degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or a related discipline.
- Programming Languages: Strong proficiency in Python is mandatory, with experience in data science libraries like NumPy, Pandas, and Scikit-learn. Knowledge of SQL is also essential for data extraction and manipulation.
- AI/ML Frameworks: Expertise deep learning frameworks such as PyTorch and TensorFlow. Familiarity with Hugging Face transformers, NLTK, or SpaCy is also common.
- Experience with LLM frameworks like LangChain and LlamaIndex.
- Proficiency in NLP techniques include embeddings, topic modeling, text classification, semantic search, and summarization.
- Cloud Platforms: Hands-on experience with major cloud computing services (AWS, Azure, GCP) for model deployment and leveraging services like Azure OpenAI, Google Vertex AI, or AWS Bedrock.