AI Engineer

3 settimane fa

turbigo, Italia Sistemi finanziari S.p.A A tempo pieno

Per società leader a livello europeo nei servizi di credit management, focalizzata su soluzioni etiche e tecnologicamente avanzate per il recupero e la valorizzazione dei crediti, stiamo selezionando un AI Engineer.Nell’ambito del potenziamento della struttura IT e dell’evoluzione delle piattaforme applicative, abbiamo necessità di avviare un percorso strutturato di introduzione dell’AI nel landscape applicativo, a partire dalla classificazione/categorizzazione dei documenti fino all’estrazione automatica di entità (entity extraction).Un successivo step evolutivo sarà lo sviluppo di capability di chat conversazionale con i documenti e la generazione automatica di documenti a partire da template aziendali, alimentati dai dati di contesto.A tal fine, ricerchiamo di un/una AI Engineer con focus su sviluppo di modelli OCR/LLM e integrazione con i sistemi legacy. La tecnologia di riferimento è quella della piattaforma Mistral (modelli SLM/LLM open, a seconda dei casi) e dell’orchestratore Windmill, con particolare attenzione ai flussi end-to-end: ingestion di dati strutturati e non strutturati, processamento AI e ritorno delle informazioni verso i sistemi core, in modalità automatica o con human in the loop.Progettare, addestrare e manutenere pipeline OCR/LLM per la classificazione dei documenti, l’estrazione di entità e la normalizzazione delle informazioni.Configurare e integrare i modelli Mistral (SLM/LLM) tramite l’orchestratore Windmill, definendo workflow robusti e riusabili.Disegnare e implementare flussi di ingestion dati (strutturati e non strutturati) dai sistemi legacy e dai repository documentali aziendali.Sviluppare e ottimizzare componenti AI-driven per:entity extraction e data enrichment;generazione automatica di documenti a partire da template corporate.Collaborare con i team Application Development e Data per integrare i risultati dei modelli nei sistemi esistenti (API, servizi, batch, event-driven).Definire, implementare e monitorare metriche di qualità dei modelli (accuracy, recall, precision, drift, ecc.) e processi di continuous improvement.Partecipare alle attività di test tecnico, UAT e validazione funzionale, collaborando con Business, QA e Compliance.Produrre la documentazione tecnica (architetture, data flow, guideline di utilizzo) e contribuire alla diffusione delle best practice AI all’interno dell’organizzazione.

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