Joined 12 years ago
Technologies: Python, Go, TypeScript, PyTorch
Linkedin: http://www.linkedin.com/in/fabmilo
Hi, I’m Fabrizio Milo, a senior AI/ML engineer, large-scale systems architect, and former technical co-founder. I’ve spent my career building production AI, ML infrastructure, and high-scale backend systems across startups and growth-stage companies.
Most recently, I’ve been building AI platforms for LLM training and fine-tuning, RAG databases, local and remote LLM inference, semantic retrieval, and agentic orchestration for business intelligence and code generation. I’ve also contributed to open source ML projects including GPT-Neo, TensorFlow and published research on synthetic data from LLMs.
Previously, I was VP of Technology at ZELIG, where I led the virtual try-on AI research roadmap and managed a cross-functional team building ML/3D systems for fashion retail. Before that, I was Head of Machine Learning Engineering at Recurrency, where I hired and led a 6-person ML/platform team and shipped demand forecasting, dynamic pricing, and recommendation systems on AWS/Snowflake/SageMaker. I also co-founded Passio, where I built the technical foundation for an on-device Nutrition-AI SDK with real-time computer vision inference.
Earlier in my career, I built scalable systems at TheRealReal and Scopely, optimized CUDA kernels at NVIDIA, and worked on real-time market-data and high-performance systems. I’m strongest where AI research, production engineering, and startup execution meet: taking ambiguous technical/product goals and turning them into shipped systems, teams, and infrastructure.
I can architect and build anything you need given enough compute and time.
The next step are: - give the agent the whole deep learning literature research and do tree search over the various ideas that have been proposed in the past. - have some distributed notepad that any of these agents can read and improve upon.
