Expert in AI/NLP/ML

• Development and maintenance of software applications in the field of Natural Language Processing (NLP), Machine Learning (ML) and/or Artificial Intelligence (AI);
• Training of custom machine learning / deep learning models based on structured and unstructured data;
• Creating automated anomaly detection systems and constant tracking of its performance;
• Processing, cleansing, and verifying the integrity of data used for analysis;
• Design the IT architecture for solitons in the NLP / ML / AI fields, and coordinate its implementation considering master- and meta-data management concepts;
• Contributing for the analysis of data management vision, strategy and policy and derive the IT requirements;
• Contributing to the design of the IT architecture considering master- and meta-data management concepts;
• Provision of expert advice and assistance in any area associated with the Artificial Intelligence and Data Warehouse technologies;
• Perform design, development and maintenance of BI and reporting software that both follow the reference architecture rules and accurately implement the specifications received in the documents of analysis provided by the business analysts of the project.

Requirements

• Master’s degree in Artificial Intelligence or similar, combined with 11 years of IT professional experience
• Excellent knowledge of Perl, Python, Matlab, R and its NLP/ML libraries (SpaCy, NLTK, scikit-learn, pandas…);
• Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks;
• Good knowledge of AWS and/or Azure, Linux, Unix and Bash;
• Good knowledge of natural language processing systems lifecycle and agile software development methodologies;
• Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures, testing methodologies and tools, such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality;
• Knowledge of query languages, (e.g. SQL, Hive, Pig, etc) and with information extraction and NoSQL databases (e.g. MongoDB, Cassandra, HBase, etc.);
• Knowledge of data visualisation tools, such as D3.js, GGplot, etc;
• Experience in the field of corpus based linguistics;
• Experience with data analytics over big datasets, non-structured databases as well as data lakes;
• Working experience with Oracle RDBMS and PL-SQL;
  
• AWS Certified Machine Learning, Microsoft Azure AI Engineer Associate or SAS Certified Professional AI and Machine Learning Certification would be considered as a strong asset
• Excellent command of the English language.