AMIGO Srl is the first Italian SME working on climate services. Founded in 2013 by two climate scientists with a wide experience in management and entrepreneurship, AMIGO has a passionate team of experts specialised in the development of innovative IT-based climate services in different sectors, i.e. energy, food and agriculture, water management, re/insurance, and infrastructure. AMIGO’s solutions synergise the best available climate data from satellite observations, modelling products, and in-situ measurements through state-of-art techniques of machine learning, statistical analysis, and numerical modelling. Co-design is the pillar of AMIGO’s innovation, to ensure that the solutions are tailored to the end user’s needs and are an added-value in the decision-making process. The company works on a number of topics including: Development and improvement of skilful climate forecasts; co-design of tools for managing climate risk for a range of sectors, e.g. renewable energy generation; early-warning systems to foster the resilience of the energy sector to climate extremes. As AI/Machine-Learning Specialist, you will build AI/Machine-Learning models, design and implement algorithms with the aim of gaining insights and extracting information from complex, geo-spatial data. You will join a highly innovative SME, collaborating with a multi-disciplinary team on a wide range of problems in different climate-sensitive sectors. Responsibility: esigning, developing and deploying new and improved AI/Machine Learning algorithms; conducting data analysis, feature engineering, and model evaluation to improve accuracy and performance; documenting models, processes, and workflows for transparency and reproducibility; managing individual project priorities, deadlines and deliverables; participating in short business trips (domestically and internationally).
LAUREA - Vecchio o nuovo ordinamento (corsi di durata compresa tra i 2 e i 6 anni)
( 06-11-2026 )
CENTRI PER L'IMPIEGO
Rovereto (TN)
Lavoro Dipendente TI
Lavoro dipendente TD
Full Time