Machine Learning Infrastructure Engineer
Uni Systems
Posted: February 9, 2026
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Quick Summary
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; Develop and maintain software applications in the field of Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL) and/or Arti.
Required Skills
Job Description
At Uni Systems, we are working towards turning digital visions into reality. We are continuously growing and we are looking for a professional Machine Learning Infrastructure Engineer to join our UniQue Brussels, Belgium team.
What will you be bringing to the team?
• 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.
Requirements:
What do you need to succeed in this position?
• Strong experience managing on-premises and/or cloud MLOps infrastructure.
• Proficient with containerization and orchestration platforms (e.g., Kubernetes, Docker, Podman, EKS, PKS).
• Experience with ML workflow tools such as MLflow, TensorFlow (TFX), or equivalents, and workflow orchestration using Airflow.
• Hands-on experience with cloud platforms (AWS and/or Azure) and infrastructure as code (Terraform, CloudFormation).
• Skilled in Python programming, Unix/Linux, and Bash scripting.
• Familiar with agile software development methodologies.
• Experience with messaging services (Kafka, Redis, RabbitMQ).
• Knowledge of data security measures, including encryption mechanisms; ML security is a plus.
• Familiarity with NoSQL databases (Elasticsearch, MongoDB, Cassandra, HBase) and query languages (SQL, Hive, Pig).
• Experience with big data analytics, unstructured databases, and data lakes.
• Proficient with monitoring and logging tools (ELK stack, Prometheus, Grafana, OpenTelemetry, CloudWatch).
• Experience with model testing and validation in production environments.
• Solid understanding of on-prem or cloud solutions for data science applications.
• Language skills: English (C1); French (C1) is an advantage.
Desirable certifications:
• AWS Certified Machine Learning.
• Microsoft Azure AI Engineer Associate
At Uni Systems, we are providing equal employment opportunities and banning any form of discrimination on grounds of gender, religion, race, color, nationality, disability, social class, political beliefs, age, marital status, sexual orientation or any other characteristics. Take a look at our Diversity, Equality & Inclusion Policy for more information.