Podstawy
AI Engineer
milano, lombardia, Italy
Firma:
JR Italy
Klient / Pracodawca:
Mia-Platform
Opublikowano: 19.05.2026
Data zamknięcia: 03.07.2026
Referencje dotyczące stanowiska: ebfdab22d58ec2dd17884535c5c33e31
Informacje o stanowisku
Lokalizacja
milano, lombardia, Italy
Firma
JR Italy
Klient / Pracodawca
Mia-Platform
Referencje dotyczące stanowiska
ebfdab22d58ec2dd17884535c5c33e31
Typ wpisu
Podstawy
Wymagane pozwolenie na pracę UE
Nie
Opublikowano
19.05.2026
Data zamknięcia
03.07.2026
Opis stanowiska
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.
Umiejętności
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