Tagcor

Python

Proficiency in Generative AI frameworks and technologies like
- Prompt Engineering – creating specific prompts to guide LLM outputs
- Fine-Tuning and Few-Shot learning – Adapting LLMs for domain-specific tasks.
- Retrieval-Augmented Generation (RAG) – Combining LLMs with external data retrieval systems
- Text-to-Text Transfer Transformation (T5) – Framework for translating tasks into text forms.
Expertise in designing and implementing chunking strategies for diverse datasets.
Strong knowledge of data embedding techniques and working experience with vector databases like Pinecone, Weaviate, or Milvus.
Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
Familiarity with cloud platforms and services for AI/ML workloads (AWS or Azure).
Experience with API integration for AI services and building scalable applications.