> ML engineer who owns problems end-to-end - from "what should we build"
> to "it's running in prod."
Agentic LLM systems for engineering @ Neural Concept
PhD, EPFL - large-scale dynamic networks (attention, anomaly detection, knowledge graphs)
Previously @ INAIT - graph-based recommendation for scientific content, search & anomaly/trend detection for finance
LLMs search & retrieval agent design knowledge graphs GNNs
Problems without an off-the-shelf answer - somewhere between a paper and a production system, solved against a real product with real users.