Senior MLOps Engineer (AI)

TL;DR

Senior MLOps Engineer (AI): Building robust ML workflows, streamlining feature creation, and standardizing ML components for a European Online Fashion & Beauty Retailer with an accent on scalability, consistency, and speed. Focus on developing infrastructure and tooling to enable ML practitioners to experiment, version, deploy, and monitor models in a reliable and automated way.

Location: Wroclaw, Poland

Company

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

What you will do

• Design and build foundational ML platform components 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.
• Build and maintain observability and reliability tooling for ML systems.
• Work closely with infrastructure, data, and security teams to ensure that ML systems are secure, compliant, and production-grade by default.

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).

Nice to have

• 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.

Culture & Benefits

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