- Model Training Fine-Tuning: Assist/Build in training and fine-tuning large language models (e.g., GPT, LLaMA) on domain-specific data to improve model accuracy and relevance.
- Data Preparation Preprocessing: Work with large datasets, perform data cleaning, tokenization, and prepare text data for model training and evaluation.
- Prompt Engineering: Experiment with and refine prompt techniques for various generative AI applications (e.g., text summarization, question answering, chatbots).
- Model Evaluation Optimization: Help in evaluating models, using metrics such as BLEU, ROUGE, and perplexity, and work to optimize models for performance and accuracy.
- Collaborate with Cross-functional Teams: Work closely with engineering and product teams to understand project requirements, and contribute to developing scalable AI solutions.
- Documentation Reporting: Document processes, model architectures, and code; assist in creating model cards and writing reports for stakeholders.
- Managing and training LLM models (e.g., fine-tuning llama3.1).
- Generating embeddings and managing semantic search via Vector DBs.