Expert in AI/ NLP/ ML

CRI Group

We are looking for an Expert in AI/ NLP/ ML to work for us in Ispra (Italy) (relocation needed)


Job Responsibilities

  • Collection of business requirements and development/customisation/deployment/maintaining/ improvement of software applications in the field of data mining, Natural Language Processing (NLP), Machine Learning (ML) and/or Artificial Intelligence (AI)
  • Interaction with the business analysts, customer, users, project leaders and developers; Interact with data stewards and other IT stakeholders to define the data rules
  • Training of custom machine learning / deep learning models based on structured and unstructured 2 data
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Design the IT architecture for solutions in the NLP / ML / AI fields, and coordinate its implementation considering master- and meta-data management concepts
  • Analysing data architecture for consistency, completeness, accuracy and reasonableness; proposing and implementing related improvements
  • Contributing for the analysis of data management vision, strategy and policy and derive the IT requirements
  • Scripting and programming, and related testing and tuning
  • Defining data controls and implement/debug/test/recommend actions to ensure data quality and integrity, and for improvement on methodology
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Contributing to the design and implementation of the analytics architecture and its solution stack (including performance aspects, physical design, capacity dimensions etc…)
  • Writing the different documentation associated with the tasks and liaise with other project teams as necessary to address cross-project interdependencies

Job Requirements

  • Excellent and proven knowledge in Python 3, package managers (PIP, Conda) and Jupyter. Knowledge of Perl, Python, Matlab, R is an asset
  • Excellent and proven knowledge in Elasticsearch and good knowledge of the other Elastic Stack components (Kibana, Beats & Logstash)
  • Excellent and proven knowledge of SQL tooling (RDBMS, NoSQL) and related query languages
  • Excellent knowledge of Data Analytics techniques and tools over big datasets, non-structured databases as well as data lakes
  • Knowledge of data visualisation tools (such as D3.js, GGplot, etc.) and/or of business intelligence tools (e.g. PowerBI, Tableau, SAS, SAP, GoodData…)
  • Knowledge of Data Management
  • Proven knowledge in Data Engineering tasks (including, but not limited to building systems and pipelines, optimisation of algorithms, definition of architectures and functional blocks aligned with software engineering best practices)
  • Proven knowledge in Natural Language Processing (NLP), Neural Networks and Deep learning libraries, and Classical Learning (e.g. Pattern search, Clustering, Classifications) algorithms
  • Proficient in continuous code delivery and unit testing and agile software development methodologies
  • Knowledge of architectural design and implementation of scalable modern data stores
  • Knowledge in at least three of the following areas: predictive (forecasting, recommendation), prescriptive (simulation), sentiment analysis, topic detection, social media crawling and processing, plagiarism detection, trends/anomalies detection in datasets, recommendation systems
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Ability to write, debug and validate code and results, to learn new approaches and technologies and to 3 scout for new solutions efficiently and fast
  • Ability to give business and technical presentations
  • Ability to apply high quality standards
  • Ability to cope with fast changing technologies used in the different activities of the unit’s Data Science Pool
  • Very good communication skills with technical and non-technical audiences
  • Analysis and problem solving skills
  • Capability to write clear and structured technical documents
  • Ability to participate in technical meetings and good communication skills
  • Ability to understand, speak and write English (B2) 


  • Specific expertise in Python 3 libraries for data management and AI (including, but not only limited to, NumPy, SciPy, Pandas, Keras and TensorFlow)
  • Specific expertise in RDBMS (e.g. Oracle DBMS, PostgreSQL or MySQL), NoSQL databases (at least ElasticSearch, MongoDB, Apache Solr), and either Graph Databases (at least Neo4j) or TripleStore Databases (at least OpenLink Virtuoso). Specific expertise in data modelling and performance tuning for analytical queries
  • Specific expertise of AWS and/or Azure, Linux and Bash. 


Any of the following trainings, certificates and standards, will be considered as beneficial for performing of tasks:

  • AWS Certified Machine Learning
  • Microsoft Azure AI Engineer Associate
  • SAS Certified Professional AI and Machine Learning Certification

The following documents / procedures will be requested to successfully complete the hiring process :

  • A copy of your university degree(s)
  • A copy of your criminal record
  • Security Clearance Procedure

EU-Nationality is mandatory for most of our job openings, but for some of them we can, also, take into consideration CVs, that acquire work permit in the location where the client is or the job should be performed



VASS Group ( is a leading digital solutions group of companies headquartered in Madrid, Spain, present in 25 countries in Europe, the Americas and Asia with more than 4,300 professionals.

VASS helps large companies in their digital transformation process, developing and executing the most innovative and scalable projects, from strategy to operations.

All our growth comes from our talented people, passion for innovation, and a constant search for improvement, always the VASS way: “Complex made simple”.

Apply now
To help us track our recruitment effort, please indicate in your cover/motivation letter where ( you saw this job posting.