Technical & Required Skills:
- Deep understanding of LLMs (e.g. transformer-based architectures).
- Demonstrated experience programmatically using LLMs to automate data labeling, classification, localization and annotation tasks.
- Strong expertise in Python for NLU, for data processing & transformation, and for statistical analysis. Familiarity with JSON, Javascript or XML.
- Experience with popular frameworks and libraries, including TensorFlow, PyTorch, Jupyter, and other relevant AI/ML tools.
- Familiarity with APIs and platforms for working with LLMs (e.g., OpenAI, Hugging Face, etc.).
- Knowledge of localization best practices and cultural nuances for different languages and regions.
- Strong understanding of LLM evaluation metrics and the ability to assess model reliability, bias, and generalizability.
- Experience working with data pipelines, automation tools, and integrating models into production systems to ensure scalable, reliable solutions.
