DGS provides valuable services and solutions in Cyber Security, Digital Solutions, and Management Consulting.
Our guiding aim is to fully satisfy customer needs, ensuring the highest excellence of solutions and maximum reliability of results.
The goal is to design the best ICT solutions capable of addressing the technological challenges of the new millennium, making innovation and excellence the hallmarks of our brand.
Our Core Values reflect the culture and shared values of the entire group, serving as beacons that constantly guide our actions and decisions.
DGS boasts over 500 clients, mostly of the Enterprise class, active in key market segments: Public Administration, Banking and Insurance, Industry, Energy and Utilities, Transport, and Telecommunications.
For the Digital Solutions business line, and specifically for our ComplEtE Competence Center, a cooperative platform managing the end-to-end supply chain, we are looking for a
We wish to connect with professionals with proven experience in software development using AI, Machine Learning, and LLM technologies.
Proficiency in Python libraries for ML / AI (TensorFlow, PyTorch) and Gen AI / LLM (e.g., OpenAI)Experience with Machine Learning models (supervised, unsupervised) and training custom modelsKnowledge of key tools for interacting with neural networksGood understanding of modern architectures based on microservicesStrong analytical skills to translate business requirements into application logicGood knowledge of ALM tools (Jira / Microsoft DevOps)Basic knowledge of relational databases; familiarity with time-series databases is a plusBasic understanding of CI / CD concepts and DevOpsExperience working in organized teams following Agile / Scrum methodologies.
Position will be commensurate with actual experience. If your resume aligns with the position, we will organize an initial interview to deepen our mutual understanding.
Otherwise, your resume will be stored in our database, and we will contact you in the future if suitable opportunities arise.
This announcement is addressed to candidates of all genders (L. 903 / 77).
#J-18808-Ljbffr