Key Responsibilities
- Design and optimize prompt templates for large language models to improve response accuracy and relevance
- Develop evaluation frameworks to assess model performance and response quality
- Collaborate with research teams to refine model training data and fine-tuning strategies
- Implement automated testing pipelines for prompt-response validation
- Document best practices for prompt engineering and model interaction patterns
- Stay updated with advancements in NLP research and apply them to production systems
Requirements
- 2+ years of experience in NLP, machine learning, or related fields
- Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, spaCy)
- Strong understanding of transformer models and prompt engineering techniques
- Familiarity with API development and integration
- Experience with evaluation metrics for language models