Machine Learning Engineer

Description

At Uni Systems, we are working towards turning digital visions into reality. We are continuously growing and we are looking for an Applications Cloud Architect to join our UniQue Brussels team!

What will you be bringing to the team?

• Our UniQue people come from a variety of different backgrounds and industries, with different skillsets and approaches, but they have one thing in common: passion for technology and innovation!
• For this Machine Learning Engineer role we expect you to:
• Be responsible for the Development and maintenance of software applications in the field of Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL) and/or Artificial Intelligence (AI)
• Design, implement and maintain a scalable, reliable and secure hybrid cloud ML Ops infrastructure to deploy, test, manage and monitor ML models in different environments
• Work closely with data scientists and back-end developers to build, test, integrate and deploy ML models
• Analyse performance metrics and troubleshoot issues to ensure high availability and reliability;
• Design CI/CD pipelines, use orchestration solutions and data versioning tool
• Create automated anomaly detection systems and constant tracking of its performance
• Design the IT architecture for solutons in the NLP / ML / AI fields, and coordinate its implementation considering master- and meta-data management concepts
• Provide security studies, security assessments or other security matters associated with information system projects;

Requirements

What do you need to succeed in this position?

• Masters Degree + 15 years of IT experience Minimum Level
  
• Excellent knowledge of managing a MLOps infrastructure.
• Excellent knowledge with application containerization, virtualization.
• Good knowledge of TensorFlow (TFX), Airflow, MLflow, Kubeflow or equivalents.
• Good knowledge of Perl, Python, Matlab, R and its NLP/ML libraries (SpaCy, NLTK, scikit-learn, pandas…).
• Good 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 Data Management.
• 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, such as SQL, Hive, Pig, etc and with information extraction.
• Knowledge of NoSQL databases, such as 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 alignment models and classification methods.
• Experience with data analytics over big datasets, non-structured databases as well as data lakes.