Senior MLOps Engineer

Are you passionate about improving the way Machine Learning systems are developed, deployed, and scaled in real-world production environments? We are collaborating with a leading European Online Fashion & Beauty Retailer to find a highly capable and self-driven Machine Learning Engineer (MLE/MLOps Focus) to join a fast-moving and impactful team working on the Home page.

• Design and build ML components, including systems for data access, feature management, model training, deployment, and inference at scale.

• Develop infrastructure and tooling that enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.

• Architect scalable, modular, and reusable systems that serve as the backbone of ML development across multiple teams.

• Implement core abstractions and APIs — from feature creation to model rollout.

• Build and maintain observability and reliability tooling for ML systems — including telemetry pipelines, model health checks, and automated retraining triggers.

• Establish best practices, frameworks, and reference implementations that raise the bar for engineering rigor and speed in ML delivery.

• Work closely with infrastructure, data, and security teams to ensure that ML systems are secure, compliant, and production-grade by default.

• 5+ years of experience in Machine Learning Engineering or MLOps roles

• Solid Python development skills

• Strong hands-on experience with Airflow (MWAA), MLFlow, and/or SageMaker

• Familiarity with ML observability tools such as Grafana, custom metric logging, model drift detection, and alerting mechanisms

• Proficiency in building CI/CD pipelines for ML systems with automated testing and validation

• Experience with Infrastructure-as-Code tools (CloudFormation, YAML)

• Understanding of secure and compliant deployment of ML pipelines

• Excellent debugging and problem-solving skills

• Experience with OpenAI API usage in production, containerization, and Kubernetes orchestration is highly valued

Benefits:

• Paid Vacation
• Hybrid Work (home/office)
• Sick Days
• Sport/Insurance Compensation
• Holidays Day Off
• English Classes
• Training Compensation
• Transportation compensation