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- Master’s degree in IT or relevant discipline, combined with minimum 15 years of relevant working experience in IT;
- Excellent knowledge of managing an on-prem and/or cloud MLOps infrastructure;
- Excellent knowledge of containerization and orchestration platforms (e.g. Kubernetes, Docker, Podman, EKS, PKS) Good knowledge of MLflow, TensorFlow (TFX) or equivalents;
- Good knowledge of Airflow, Python, Unix and Bash;
- Good knowledge of AWS and/or Azure;
- Good knowledge of IaC (Terraform, CloudFormation);
- Good knowledge of messaging services and platforms (e.g. Kafka, Redis, RabbitMQ);
- Knowledge of data security measures (knowledge of encryption mechanisms and ML security is considered a plus);
- Knowledge of NoSQL databases, such as Elasticsearch, MongoDB, Cassandra, HBase;
- Knowledge of query languages, such as SQL, Hive, Pig, etc. and with information extraction;
- Experience with data analytics over big datasets, non-structured databases as well as data lakes;
- Experience with monitoring and logging tools (e.g. ELK stack, Prometheus, Grafana, OpenTelemetry, CloudWatch);
- Optional Certifications: 1) AWS Certified Machine Learning, 2) Microsoft Azure AI Engineer Associate;
- Excellent command of the English language, French would be an advantage.
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