MLOps / LLMOps Engineer
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• Design, build, and maintain production-grade ML systems, with a strong focus on LLMs across secure hybrid on-premises and cloud environments.
• Deploy, test, monitor, and manage ML models in containerised environments.
• Develop and improve the LLMOps lifecycle, covering data preparation, fine-tuning, evaluation, deployment, and monitoring.
• Build evaluation frameworks to assess LLM quality, robustness, and regression performance.
• Design CI/CD pipelines and implement orchestration, automation, and data versioning solutions.
• Monitor system performance, troubleshoot issues, and ensure high availability and reliability.
• Optimise ML pipelines for scalability, efficiency, and cost-effectiveness.
• Contribute to security assessments and support secure AI infrastructure practices.
• Collaborate with Data Scientists and Back-end Developers to integrate and deploy ML models.
• Provide technical guidance and support to team members on MLOps / LLMOps best practices. 🔹 What are we looking for?
• Minimum education requirement: Bachelor’s degree in Computer Science, Information Technology, Systems Engineering, or a related field.
• Strong experience managing on-premises and/or cloud-based MLOps / LLMOps infrastructure.
• Experience with containerisation and orchestration technologies such as Kubernetes, Docker, Podman, EKS, or PKS.
• Knowledge of ML lifecycle tools such as MLflow, TensorFlow Extended (TFX), or equivalent solutions.
• Experience with AWS or EU cloud providers and workflow orchestration tools such as Airflow.
• Good knowledge of Python, Unix, and Bash scripting.
• Experience with CI/CD, Agile methodologies, and Infrastructure as Code tools such as Terraform or CloudFormation.
• Familiarity with messaging platforms such as Kafka, Redis, or RabbitMQ.
• Experience with monitoring and logging tools such as ELK Stack, Prometheus, Grafana, OpenTelemetry, or CloudWatch.
• Knowledge of SQL, NoSQL databases, data lakes, and large-scale data processing.
• Understanding of data security, encryption mechanisms, and ML security principles.
• Experience with model testing, validation, and monitoring in production environments.
• Ability to produce clear, structured technical documentation. ⭐ Nice to have: Knowledge of the European Commission’s grant management ecosystem, particularly eGrants. 📌 Important
requirements:
• EU citizenship is mandatory.
• Relocation to Brussels is required.
• The role follows a near-site working model. Interested in helping deliver reliable, secure, and scalable AI solutions? 📩 Apply now
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