Large Language Models (LLMs) - architecture and evaluation

Python programming for ML/AI applications

Machine Learning frameworks (PyTorch, TensorFlow)

Natural Language Processing (NLP) techniques and tools

Statistical analysis and data visualization

Hugging Face Transformers library

Benchmark design and evaluation metrics

SQL and data management

Version control systems (Git)

Cloud platforms (AWS, GCP, or Azure)

Prompt engineering and testing methodologies

Model evaluation frameworks and tools

Strong analytical and problem-solving abilities

Excellent communication and presentation skills

Ability to work collaboratively in cross-functional teams

Attention to detail and commitment to quality

Leadership and mentoring capabilities

Research mindset with curiosity for continuous learning

Project management and organizational skills

Ability to translate complex technical concepts for diverse audiences

Critical thinking and objective assessment abilities

Adaptability to rapidly evolving AI/ML landscape