AISB-774 Senior MLOps / AI Engineer

We are looking for a Senior MLOps / AI Engineer to design, deploy and maintain secure, scalable and highly available hybrid MLOps infrastructures. The role sits at the crossroads of cloud computing, AI, machine learning and large-scale data architectures within a demanding technical environment., * Design, implement and maintain a scalable, reliable and secure hybrid MLOps infrastructure to deploy, test, manage and monitor ML models across multiple environments.

• Develop and maintain software applications in NLP, Machine Learning, Deep Learning and Artificial Intelligence.
• 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 and maintain CI/CD pipelines, orchestration solutions and data versioning tools.
• Build automated anomaly detection systems, continuously monitor performance and optimise ML pipelines for scalability, efficiency and cost-effectiveness.
• Design IT architectures for NLP / ML / AI solutions and coordinate their implementation, taking master- and metadata management concepts into account.
• Deliver security studies, security assessments and address other security aspects related to information system projects.
• Provide guidance, support and expertise to team members on MLOps best practices.

• Master's degree in IT, Computer Science, Engineering or equivalent with specialization in AI, MLOps or data engineering, or an advanced degree in NLP, computational linguistics or machine translation.
• Minimum 13 years of professional IT experience.
• Excellent knowledge of managing on-premise and/or cloud-based MLOps infrastructures.
• Strong expertise in containerization and orchestration platforms (Kubernetes, Docker, Podman, EKS, PKS).
• Good knowledge of MLflow, TensorFlow (TFX) or equivalent frameworks.
• Good knowledge of Airflow.
• Strong knowledge of AWS and/or Azure.
• Excellent Python skills.
• Good knowledge of Unix and Bash.
• Good understanding of Agile software development methodologies.
• Good knowledge of Infrastructure as Code (Terraform, CloudFormation).
• Good knowledge of messaging platforms (Kafka, Redis, RabbitMQ).
• Knowledge of data security, encryption mechanisms and ML security (considered a plus).
• Knowledge of NoSQL databases (Elasticsearch, MongoDB, Cassandra, HBase).
• Knowledge of query languages (SQL, Hive, Pig) and information extraction techniques.
• Experience with big data analytics, unstructured databases and data lakes.
• Experience with monitoring and logging tools (ELK stack, Prometheus, Grafana, OpenTelemetry, CloudWatch).
• Experience with model testing and validation in production environments.
• Ability to produce clear, structured technical documentation.
• Excellent communication skills with both technical and non-technical stakeholders.
• Strong analytical, problem-solving skills and ability to adapt to rapidly evolving technologies.

Preferred Certifications

• AWS Certified Machine Learning.
• Microsoft Azure AI Engineer Associate.