Machine Learning
Pubblicato il 12-08-2026 - Tmc in Italia
About This Vacancy You will work at the intersection of data science, software engineering, and cloud technologies, transforming machine learning models into robust, production-ready applications. Collaborating with cross-functional teams, you will develop end-to-end ML pipelines, optimize model performance, and ensure the reliability, scalability, and efficiency of AI-powered systems.
- Define machine learning system requirements, solution architectures, and technical specifications based on business and project objectives.
- Perform data analysis, model feasibility assessments, and technology evaluations to support the development of scalable AI and machine learning solutions.
- Design, develop, deploy, and optimize machine learning models, automated ML pipelines, and production-ready AI applications aligned with project goals.
- Conduct model testing, validation, monitoring, troubleshooting, and technical documentation to ensure the reliability, scalability, performance, and maintainability of machine learning solutions in production environments.
What We Expect From You
- MSc or PhD in Computer Science, Applied Mathematics or equivalent
- Previous industry experience is considered a plus
- Strong working knowledge of Python, Matlab, R
- Working knowledge of common machine learning frameworks such as TensorFlow, PyTorch, Apache Spark, Keras
- Proven experience in modeling physical-technical problems, risk modeling, algorithm development, image processing and / or data analysis is considered a plus
- Experience with image processing is considered a plus
- Good oral and written communication skills, both in Italian and English.
What You Can Expect From Us The position offers a permanent employment contract, and the base gross annual salary (Gross Annual Salary – RAL ) will be no less than €32,000 , in line with the National Collective Bargaining Agreement (CCNL) for Commerce – Tertiary, Distribution and Services .
TMC is committed to offering a competitive compen