Ai/Ml Engineer

Fincons Group is an IT business consulting company that has been designing the digital future of leading companies on international markets for 40 years.
Fincons Group built its reputation on foreseeing and interpreting new business models and the rapid evolution of IT systems by building a complete range of services: from research and consulting to design and development, from system integration of leading vendor software solutions right up to application management, supporting clients step by step along their digital transformation journey.
Fincons is a multinational with over 2,600 people and several offices worldwide (in Italy, Switzerland, Germany, France, the United Kingdom, Belgium and the USA), but above all a Family Company where the founders play a strategic role with commitment and passion, grounding the company in the same principles of a united and caring family.
We firmly believe in the value of cooperation and in the contribution that every idea and intuition can bring.
We believe that everyone s effort can make a difference.
Transforming knowledge into a strategic resource is our company mission, and we pursue it with the help of our most strategic asset: our people.
To support our customer, we are looking for a: AI/ML ENGINEER - Normal TASKS: Develop, train, deploy, and maintain NLP, AI, Machine Learning, LLM, and Generative AI solutions, including RAG-based architectures and software applications for business use cases.
Build, optimize, deploy, and monitor machine learning models, classifiers, and anomaly detection systems, implementing MLOps and CI/CD practices to automate the model lifecycle, ensure scalable deployments, detect model drift, and support continuous retraining.
Process, govern, and enhance data quality by defining data rules and controls, collaborating with stakeholders, ensuring data integrity, assessing data architectures, and mitigating bias in datasets and AI models.
Design and coordinate the technical architecture of AI/ML solutions, working with engineering teams while applying data management and governance best practices.
Improve and innovate AI capabilities through machine translation quality enhancements, applied research, evaluation of emerging technologies, and adoption of cutting-edge AI/ML methodologies.
Draft technical documentation, communicate results, and ensure compliance with data protection and AI regulations while engaging both technical and non-technical stakeholders.
REQUIREMENTS: Excellent knowledge of Python, R, and major AI/ML libraries and frameworks, including TensorFlow, PyTorch, scikit-learn, pandas, SpaCy, and NLTK.
Strong expertise in machine learning, deep learning, and AI algorithms, including classification models, neural networks, and predictive analytics techniques.
Excellent knowledge of Generative AI, Large Language Models (LLMs), Small Language Models (SLMs), and related AI frameworks and architectures.
Good knowledge of Natural Language Processing (NLP) methodologies, tools, and the end-to-end NLP system lifecycle.
Strong experience in designing, deploying, and monitoring AI/ML solutions, applying MLOps practices for model versioning, governance, performance monitoring, and lifecycle management.
Excellent knowledge of DevOps principles, CI/CD automation, containerization technologies, and deployment pipelines using tools such as GitLab and Docker.
Excellent knowledge of data governance, data quality, data lifecycle management, and data preparation processes for AI and analytics projects.
Strong experience with SQL and NoSQL databases, big data environments, data lakes, and analytics on large structured and unstructured datasets.
Experience with cloud-based AI platforms and services, including AWS and Azure solutions for model training, fine-tuning, deployment, and LLM development.
Good knowledge of business intelligence, data visualization, and reporting tools, including Power BI, Qlik Sense, Plotly, and Matplotlib.
Experience in delivering AI, machine learning, and advanced analytics projects within complex organizations, including public-sector environments.
Understanding of AI governance, AI Act requirements, AI risk management, cybersecurity principles, and AI safety and compliance best practices.
CERTIFICATES: (Optional) One of the following or an equivalent certification: AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, SAS Certified Professional AI and Machine Learning.
SKILLS: Excellent communication and interpersonal skills, with the ability to collaborate effectively in multicultural and multilingual environments.
Ability to understand, speak, and write English and Italian proficiently, with Spanish considered an additional asset.
Strong technical communication skills, including the ability to produce clear documentation, guidelines, reports, and presentations for both technical a