AI Engineer

LLM & NLP Expertise

• Hands-on experience with Large Language Models (GPT, LLaMA, BERT, etc.).
• Strong understanding of transformer architectures.
• Experience in fine-tuning LLMs for tasks like summarization, sentiment analysis, translation, and conversational AI.

Prompt Engineering

• Ability to design and optimize prompts for LLM-based applications.

NLP Libraries & Frameworks

• Proficiency with Hugging Face Transformers, spaCy, NLTK, and OpenAI API.

Vector Databases & Semantic Search

• Experience with FAISS, Pinecone, embeddings, and tokenization.

Model Optimization

• Techniques like quantization and distillation.

ML Ops Practices

• Model lifecycle management: versioning, monitoring, CI/CD pipelines.
• Familiarity with Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).

Deployment Experience

• Successfully deployed at least one LLM-based application to production.

Responsible AI & Compliance

• Knowledge of ethical AI standards, data privacy regulations, and GDPR.