Expert in AI/ML/NLP (SNS02314)
Job Description
Following tasks will be performed by the external service provider:
• Design the IT architecture for solutions in the NLP / ML / AI fields, and implement PoCs
such as in the ChatBot / RAG field;
• Analyse data assets & business processes;
• Analyse risk-level of existing LLMs implemented in few of IT systems;
• Industrialise PoCs once they have proven to bring value-added, in close collaboration with
other engineers members.
• Train custom machine learning (e.g. RAG based) based on structured and unstructured data;
• Interact with the local data correspondent, the digital transformation officer, and other IT
stakeholders;
• Process, cleanse, and verify the integrity of data used for analysis;
• Follow the progress of implementation of corporate AI initiatives and identify
opportunities to leverage the use of them;
• Contribute to the analysis of data management vision, strategy and policy and derive the IT
requirements.
Knowledge and Skills:
Following knowledge & skills are mandatory for the performance of the above listed tasks:
Knowledge:
• Very good knowledge of Python. Knowledge of R and its NLP/ML libraries is a plus (e.g.:
SpaCy, NLTK, scikit-learn, pandas…);
• Very good knowledge of machine learning techniques and algorithms, such as SVM, Neural
Network, and/or artificial intelligence frameworks;
• Very good knowledge of Data Management;
• Good knowledge of AWS and/or Azure;
• Good knowledge of Linux;
• Good knowledge of natural language processing systems lifecycle and agile software
development methodologies;
• Good knowledge of NoSQL databases, such as MongoDB;
• Good knowledge of graph DB and triples;
• Good knowledge of query languages, such as SQL, Hive, Pig, etc.;
• Knowledge of data visualisation tools, such as D3.js, GGplot, etc.;
• Experience with data analytics over big datasets, non-structured databases as well as data
lakes; Skills:
• Ability to participate in multilingual meetings;
• Ability to understand, speak and write English, optionally French as an additional asset;
• Excellent interpersonal and communication skills,
• Ability to work in a team as well as autonomously;
• Results-oriented mindset, focused on delivering;
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.; • Good
scripting and programming skills;
• Data-driven mindset.
Specific Expertise:
Any experience in the field of RAG processing will be considered as an asset.
Hiring Team Member
