AI Expert

AI Expert

Netcompany-Intrasoft

Brussels, Belgium

As an AI Expert, you will:

• Implement and manage a scalable, reliable, and secure hybrid cloud MLOps infrastructure for deploying, testing, and monitoring ML models across diverse environments;
• Develop and maintain cutting-edge software applications leveraging Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL) techniques;
• Collaborate closely with Data Scientists and Back-End Developers to seamlessly build, test, integrate, and deploy production-ready ML models;
• Analyze performance metrics, troubleshoot issues, and ensure the high availability and reliability of all deployed ML systems;
• Design and implement robust CI/CD pipelines, utilize orchestration solutions, and manage data and model versioning for repeatable workflows;
• Create and constantly track the performance of automated anomaly detection systems, while optimizing ML pipelines for scalability and cost-efficiency;
• Lead the IT architectural design for all NLP/ML/AI solutions, incorporating best practices for master- and meta-data management;
• Ensure system security through assessments and studies, and provide expert MLOps support and guidance to empower the development team.

Qualifications:

What would make you a fit for the role:

• University degree in IT, Computer Science, Engineering, or equivalent, preferably specializing in AI with at least 4 years of professional experience;
• Excellent knowledge of managing and maintaining both on-premise and cloud MLOps infrastructure (AWS/Azure);
• Expertise in containerization (Docker, Podman) and orchestration platforms (e.g., Kubernetes, EKS, PKS), along with proficiency in MLOps tools like MLflow or TFX;
• Strong proficiency in workflow orchestration (Airflow), Infrastructure as Code (Terraform/CloudFormation), and effective use of messaging platforms (Kafka, Redis) for pipeline efficiency;
• Excellent command of Python, coupled with proficiency in Unix and Bash scripting for system management and automation;
• Experience with Big Data analytics, utilizing non-structured databases (NoSQL like MongoDB, Elasticsearch), data lakes, and proficiency in query languages (SQL, Hive);
• Hands-on experience with monitoring and logging tools (e.g., ELK stack, Prometheus, Grafana) and robust experience with model testing and validation in production environments;
• Proven ability to produce clear, structured technical documentation and possess excellent communication skills in English.