Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building robust ML workflows and standardizing ML components for a leading European Online Fashion & Beauty Retailer with an accent on scalability, consistency, and speed across the organization. Focus on infrastructure and tooling that enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.

Location: Central Europe

Company

hirify.global is collaborating with a leading European Online Fashion & Beauty Retailer.

What you will do

• Design and build foundational ML platform 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 to standardize how ML workflows are executed — 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.

Requirements

• 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

Nice to have

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

Culture & Benefits

• Paid Vacation
• Sick Days
• Floating Holidays
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation