Climate AI/ML Specialist for Forecasts & Risk Tools

Agenzia del Lavoro Trentino; Rovereto; On-site; EUR 30,000 - 35,000; Full time

Job summary

AMIGO Srl is seeking an AI/ML Specialist in Rovereto, Italy, to build and deploy machine-learning models on geo-spatial climate data. You will work with a multidisciplinary team, focusing on climate service solutions across energy, agriculture, water, and infrastructure sectors.

The role requires a MSc in a quantitative discipline, 3+ years of relevant experience, and proficiency with PyTorch, scikit-learn, and Python. Knowledge of Xarray/GeoPandas and Docker is essential.

Qualifications

• MSc in a quantitative field (e.g. mathematics, physics, engineering).
• 3+ years of professional experience in similar AI/ML roles.
• Experience with AI/ML frameworks (PyTorch, scikit-learn, Keras, etc.).
• Proficiency in Python and libraries like Xarray and GeoPandas; strong visualization skills.
• Excellent problem-solving and communication abilities; English proficiency at C1.
• Certifications in AI/ML are desirable; familiarity with Docker and containers.

Responsibilities

• Design, develop and deploy AI/ML models and algorithms for climate services.
• Perform data analysis, feature engineering and model evaluation to improve accuracy.
• Document models, processes and workflows for reproducibility.
• Manage project priorities, deadlines and deliverables; participate in travel as needed.

Skills

Python

AI/ML frameworks

PyTorch

scikit-learn

Keras

Xarray

GeoPandas

Visualization

English (C1)

Problem solving

Communication

Docker

Education

MSc in a quantitative discipline

PhD is a plus

Tools

Docker

Containers

Job description

AMIGO Srl is seeking an AI/ML Specialist in Rovereto, Italy, to build and deploy machine-learning models on geo-spatial climate data. You will work with a multidisciplinary team, focusing on climate service solutions across energy, agriculture, water, and infrastructure sectors.

The role requires a MSc in a quantitative discipline, 3+ years of relevant experience, and proficiency with PyTorch, scikit-learn, and Python. Knowledge of Xarray/GeoPandas and Docker is essential.