Básico

AI Engineer

milano, lombardia, Italy Compañía: JR Italy Cliente / Empleador: Mia-Platform
Publicado: 19.05.2026
Fecha de cierre: 03.07.2026
Referencia laboral: ebfdab22d58ec2dd17884535c5c33e31

Información del puesto

Ubicación
milano, lombardia, Italy
Compañía
JR Italy
Cliente / Empleador
Mia-Platform
Referencia laboral
ebfdab22d58ec2dd17884535c5c33e31
Tipo de listado
Básico
Se requiere permiso de trabajo de la UE
No
Publicado
19.05.2026
Fecha de cierre
03.07.2026

Descripción del puesto

The role We are looking for an AI Engineer , to join our Mia-Platform group. Specifically, the person will work on our Mia-Care Team. As a AI Engineer, you'll be at the core of what makes Mia-Care tick. Our platform uses LLMs to analyze medical device software, identify compliance gaps, and suggest actionable remediations. You'll own the intelligence layer that makes this possible — from model selection and fine-tuning to production deployment and cost optimization. This isn't a role where you plug in an API and call it a day. You'll be shaping how AI works inside a highly specialized, high-stakes domain, where quality and reliability are non-negotiable. Responsibilities Design, fine-tune and evaluate LLMs for domain-specific tasks in medical device software analysis. Craft and validate prompts that drive gap analysis and remediation workflows — iterating rigorously until the output is something you'd stake your reputation on. Own the full MLOps lifecycle : model versioning, monitoring, evaluation pipelines, and continuous improvement Optimize for cost and scalability: you'll obsess over inference efficiency, latency, and making sure what you build can grow without burning the budget. Build AI pipelines that are reliable, observable, and production-grade from day one. Collaborate directly with product and domain experts to translate regulatory complexity into AI-solvable problems — no translation layer, no ticket queue.

Habilidades

Agile Project Management Algorithms analyse big data analyse business requirements apply ICT systems theory apply systemic design thinking Artificial Neural Networks Assembly (computer programming) assess ICT knowledge build business relationships build predictive models build recommender systems Business Analytics Business Intelligence business process modelling C COBOL CoffeeScript Common Lisp computer programming Computer Simulation Computer Vision create data sets creatively use digital technologies Data Mining Data Models Data Science database development tools Deep Learning define technical requirements deliver visual presentation of data design application interfaces design database scheme design process develop creative ideas develop statistical software digital data processing Erlang Groovy Haskell ICT project management methodologies identify processes for re-engineering Information Architecture information categorisation Information Extraction information structure Java (computer programming) JavaScript lean project management LINQ Lisp manage business knowledge manage ICT data classification manage ICT semantic integration Matlab Microsoft Visual C++ ML (computer programming) N1QL Objective-C OpenEdge Advanced Business Language operational research Pascal (computer programming) perform dimensionality reduction Perl PHP principles of artificial intelligence Process-based management Prolog (computer programming) Python (computer programming) R resource description framework query language Ruby (computer programming) SAP R3 SAS language Scala Scratch (computer programming) Smalltalk (computer programming) SPARQL Swift (computer programming) systems development life-cycle task algorithmisation TypeScript Unstructured Data use data processing techniques utilise machine learning VBScript Visual Basic visual presentation techniques

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