Ai Research Scientist vs AI Engineer

Ai Research Scientist

LLM Post Training Reinforcement Learning From Feedback Foundation Model Fine Tuning Large Language Model Research Model Evaluation Design Distributed Training Optimization Multimodal Model Development Research Prototype Development Benchmark Framework Development Scientific Experimentation Research Publication Delivery Generative AI Research Model Alignment Methods Federated AI Systems Agentic AI Architectures Statistical Model Evaluation Offline Metrics Analysis Adversarial Testing Analysis Annotation Quality Analysis PyTorch Model Development DeepSpeed Distributed Training Megatron LM Training Hugging Face Transformers CUDA Performance Optimization Python Research Tooling

AI Engineer

Fine-tuning and prompt engineering LLM integration and API usage Agentic AI system design Machine learning model development Data preprocessing and feature engineering Model evaluation and performance tuning Problem decomposition and systems thinking Technical communication and documentation Large language model architecture AI ethics and responsible deployment Computer vision or NLP specialization Linear algebra and calculus fundamentals Statistics and probability Data analysis and visualization Python and core ML libraries (scikit-learn, PyTorch, TensorFlow) Cloud ML platforms (AWS SageMaker, Google Vertex AI) MLOps and model deployment pipelines Docker and containerization SQL and NoSQL databases