Machine Learning Engineer

My International client based in Brussels is seeking a Machine Learning Engineer ( NLP and AI ) to join the team on a long term contract assignment. This is a hybrid role with off-site and on-site working.

Assignment tasks and responsibilities of the ML Engineer

• 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.
• 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).
• 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 tools.
• Creating automated anomaly detection systems and constant tracking of its performance and optimising ML pipelines for scalability, efficiency and cost-effectiveness.
• Design the IT architecture for solutions in the NLP / ML / AI fields, and coordinate its implementation considering master- and meta-data management concepts.
• Provision of security studies, security assessments or other security matters associated with information system projects.
• Provision of support and guidance to other team members on MLOps practices.

The customer seeks candidates with the following skills and experience:

• Master's degree in IT and minimum 15 years of relevant experience (or Bachelor's in IT and minimum 19 years of experience).
• One of the following: University degree in NLP (computer science or computational linguistics), Specialisation in (statistical/neural) machine translation (MT), or University degree in IT / Computer Science / Engineering with specialisation in AI, ML operations or data engineering.
• Strong experience managing on-prem and/or cloud-based MLOps infrastructure.
• Hands-on experience with containerisation and orchestration tools (e.g. Kubernetes, Docker, Podman, EKS, PKS).
• Proficient in MLflow, TensorFlow (TFX), and Airflow.
• Solid experience with AWS and/or Azure.
• Proficient in Python, Unix, and Bash scripting.
• Experienced in handling large-scale, unstructured data and data lakes.
• Familiar with monitoring/logging tools (e.g. ELK, Prometheus, Grafana, OpenTelemetry, CloudWatch).
• Skilled in model testing and validation in production environments.
• Good understanding of Agile development methodologies.
• Experienced with Infrastructure as Code (Terraform, CloudFormation).
• Knowledge of messaging platforms (Kafka, Redis, RabbitMQ).
• Understanding of data security (encryption, ML security a plus).
• Familiar with NoSQL databases (e.g. Elasticsearch, MongoDB, Cassandra, HBase).
• Experience with query languages (SQL, Hive, Pig) and information extraction.
• Excellent English (C-level, written and spoken