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.
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Prompt Engineer • Delhi, Delhi, India
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