MLOps Engineer
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Key Responsibilities
Design, deploy, and operate scalable ML and LLM platforms. Manage the full ML/LLM lifecycle, from training and evaluation to deployment and monitoring. Build and maintain CI/CD pipelines for machine learning solutions. Collaborate with Data Scientists and Software Engineers to deploy AI models into production. Monitor model performance, reliability, and operational efficiency. Implement automation, orchestration, and infrastructure-as-code solutions. Ensure platform security, compliance, and operational best practices. Produce technical documentation and support team adoption of MLOps/LLMOps practices. Key Skills MLOps / LLMOps Kubernetes, Docker, Podman MLflow, TensorFlow (TFX) Airflow Python, Bash, Linux AWS or Cloud Platforms Terraform, CloudFormation Kafka, RabbitMQ, Redis OpenSearch, MongoDB SQL Prometheus, Grafana, ELK, OpenTelemetry Model Deployment, Monitoring & Validation Education Bachelor's degree (EQF Level 6) or higher in Computer Science, Information Technology, Systems Engineering, or a related field. Nice to Have Experience with Data Lakes and large-scale data platforms. Knowledge of AI/ML security and encryption mechanisms. Experience within European Commission environments (eGrants). Required skills Machine Learning Orchestration MLFlow llm Containerization Languages English (Proficient)
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MLOps / LLMOps Engineer
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Brussels, Brussels Region, BRU, Belgique SoftNice Temps pleinWe are looking for a DevOps Engineer to design, implement, and support secure, scalable cloud and hybrid infrastructure solutions supporting AI/ML platforms and business-critical applications. **Key Responsibilities** Build and maintain cloud and hybrid infrastructure environments. Develop CI/CD pipelines and Infrastructure as Code solutions. Support...