Summary
Balázs Fehér is a Staff Data Scientist and AI/ML lead based in London with a decade of experience building and productionising machine learning systems across finance, pharmaceuticals and enterprise SaaS. He specializes in transformer-based NLP, Generative AI, LLM fine-tuning and Retrieval-Augmented Generation pipelines, moving models from PoC to high-throughput production with strong MLOps practices. His background spans anomaly detection for banking, document information extraction for biotech and distributed training/optimization on cloud platforms like AWS SageMaker. A former cognitive neuroscience PhD, he brings a rigorous experimental mindset to model design and evaluation, especially in robustness and monitoring. Colleagues rely on him to reconcile research-grade models with engineering constraints—often squeezing efficiency gains through quantization and hyperparameter tuning. Currently shaping AI efforts at Insig AI after recent roles leading LLM transitions at Arietta.ai and Neural Machines.
10 years of coding experience
10 years of employment as a software developer
Machine Learning Engineer, Machine Learning Engineer at Udacity
Doctor of Philosophy (PhD) Cognitive Neuroscience, Doctor of Philosophy (PhD) Cognitive Neuroscience at Universität des Saarlandes
English, German, Hungarian, Tibetan, Chinese