Collaborates with the technical team to implement both traditional machine learning and generative AI systems under senior guidance.
This role supports the entire AI development process, from data collection and preprocessing through model deployment and monitoring for both predictive and generative applications. The Engineer builds and refines prompt templates for various LLM use cases while implementing retrieval-augmented generation systems to enhance generative applications with external knowledge. They contribute to solution development using established frameworks and model architectures, focusing on feature engineering for traditional ML and context engineering for generative applications.
This position involves conducting comparative evaluations between traditional machine learning approaches and generative AI alternatives to determine optimal solutions for specific business problems. The Engineer maintains comprehensive documentation of code, methodologies, and experimental results for both AI and generative AI implementations. They actively participate in code reviews and knowledge-sharing sessions while staying current with emerging trends across the AI/GenAI landscape. Throughout the software development lifecycle, the Engineer implements AI-assisted tools and workflows to enhance productivity and quality, collaborating across teams to integrate these capabilities into existing systems.
Mandatory
- 2+ years of experience in AI/GenAI/ML development roles, with demonstrated experience in generative AI;
- Experience implementing AI/GenAI features throughout different phases of software development;
- Solid understanding of fundamentals across machine learning, deep learning, and generative AI;
- Proficiency in Python programming with experience using TensorFlow, PyTorch, Keras, and LangChain;
- Working knowledge of prompt engineering techniques for LLMs and other generative models;
- Good understanding of relational and vector databases for AI/GenAI applications.
Preferred
- Basic knowledge of Java, C#, Go, or Node.js for AI/GenAI integration;
- Familiarity with version control systems and collaborative development workflows;
- Experience with AI-assisted software development tools and workflows;
- Clear communication skills for presenting technical findings on AI/GenAI implementations;
- Basic understanding of ML/GenAI deployment processes and monitoring requirements;
- Eagerness to learn and adapt to rapidly evolving AI/GenAI technologies;
- Bachelor's degree or higher in relevant field (or equivalent practical experience).
Location: Milano, Roma, Torino, Pisa, Napoli, Treviso, Cosenza, Genova, Bari, Salerno, Bologna.
