WHAT WE ARE LOOKING FOR

Are you ready to apply your AI/ML expertise to tackle one of the most pressing global challenges?
Join our dynamic and innovative team at CMCC, where your proactivity and technical skills can drive tangible outcomes in climate risk research. Over the past decade, CMCC has experienced significant growth, and we are now embarking on an exciting journey to integrate AI/ML models into multi-risk assessment frameworks within the context of climate change.
We are looking for an AI/ML Developer who will support cutting-edge research initiatives by collaborating with our multidisciplinary team to design, implement, and optimize machine learning applications for climate data analysis and multi-risk modelling. This role offers a unique opportunity to develop your expertise in AI/ML while contributing to impactful projects in a fast-paced and collaborative environment. You will play a critical role in advancing the application of big data and artificial intelligence for climate risk and multi-hazard risk assessment.

ABOUT US

CMCC Foundation is a cross-cutting scientific research center on climate change and its interactions with the environment, society, the world of business, and policymakers. Our work aims to stimulate sustainable growth, protect the environment, and develop strategies for the adaptation and mitigation of climate change. CMCC’s core objective is to conduct cutting-edge science, to train the next generation of scientists at both national and international levels, and to be a beacon for climate modelling.
CMCC pursues fundamental and applied science with utmost scientific integrity, prioritizing data-driven science and providing data, information, and research results that can support informed public debate and decision-making processes. To achieve climate research objectives at the highest international standards, we invest in training all our talents, and strive to create a workplace where everyone can excel.
At CMCC you will find a strong, professional environment. Join an inclusive community that values diversity, where every voice is heard and respected. Help foster a culture of innovation and societal change, where individuals from all backgrounds can thrive and succeed.
Over the last decade, CMCC has experienced extraordinary growth. We are now embarking on a new chapter of our journey that will further boost CMCC’s global position in climate change research…Together!

REQUIREMENTS

• PhD or Master’s degree in Computer Science, Computer Engineering, or a related research field;
• Experience with language models and NLP, including transformer-based architecturesFamiliarity with LLM application stacks, such as RAG architectures, vector databases (e.g. FAISS, ChromaDB), and orchestration frameworks (e.g. LangChain)Proven experience in machine learning model development, feature engineering, and model evaluation;
• Strong proficiency in Python and key libraries such as numpy, pandas, xarray, scikit-learn, and matplotlib;
• Hands-on experience with deep learning frameworks like PyTorch, TensorFlow, or Keras;
• Experience with geospatial data processing tools and GIS analysis;
• Solid understanding of (geo)statistics and the ability to work with climate or environmental datasets;
• Excellent knowledge of English language;
• Ability to work independently as well as collaboratively in a team environment;
• High level of accuracy, analytical thinking, and attention to detail.

ROLE

As an AI/ML Developer, you will work closely with the RAAS (Risk Assessment and Adaptation Strategies) research team, contributing to the development of advanced machine learning models tailored to climate multi-hazard risk assessment.

RESPONSIBILITIES

The AI/ML Developer will support the RAAS research team, with:

• Preprocess and prepare diverse datasets, ensuring data quality and consistency for ML models;
• Design, develop, and implement machine learning models using established framework (e.g. PyTorch, TensorFlow, Keras), while adapting state-of-the-art algorithms;
• Develop and optimize pipelines for document embedding, chunking, and retrieval in LLM-based systems;
• Integrate machine learning models into existing software systems and digital twin platforms used for climate data analysis;
• Stay up to date with the latest AI/ML/LLM research, tools, and techniques, and apply cutting-edge methodologies to climate risk problems;
• Contribute to scientific publications and research papers based on project findings;
• Participate in internal knowledge sharing and contribute to the team’s collective expertise.