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Your tasks: Develop and maintain NLP, ML, and AI applications; Train and optimize machine learning and deep learning models on structured and unstructured data; Perform feature engineering and build optimized classifiers; Enhance machine translation quality through targeted studies, customer-driven improvements and systematic evaluation; Define data rules, controls, and governance in collaboration with IT and data stakeholders; Ensure data quality, integrity and reliability through validation and cleansing; Design and monitor automated anomaly detection systems; Apply advanced data mining techniques; Design and assess NLP/ML/AI IT architectures, including master and metadata management; Contribute to data management strategy, policies and derived IT requirements; Manage project risks, issues, changes, and decisions with proper documentation; Support business case development, project initiation and solution design through business process improvement. Requirements: Master's degree in IT or relevant discipline, combined with minimum 15 years of relevant working experience in IT; At least 3 years of experience in analyzing, comparing and recommending AI models, architectures and technical solutions, considering performance, operational constraints and risk; At least 3 years of experience in developing interfaces with model serving endpoints and LLM APIs; At least 3 years of hands-on experience in evaluating and optimizing AI models, including hyperparameter tuning and resolving model output issues; At least 3 years of experience in machine learning techniques and algorithms, including supervised, unsupervised, semi-supervised and reinforcement learning models (e.g. k-NN, Naive Bayes, SVM, Decision Forests, Neural Networks, AI frameworks); At least 3 years of experience in Python; At least 3 years of experience using AWS or Azure, including AI-related services such as ML pipelines, managed training, inference and data storage; At least 3 years of recent experience in software development projects (from 2016 onward); At least 3 years of recent experience in SQL, distributed/big-data SQL engine, and information extraction (from 2016 onward); At least 3 years of experience in Unix and Bash; At least 2 years of experience in data management, including collecting, preprocessing, cleaning and organizing large datasets using coding and non-coding tools;