Data & Machine Learning Engineer (AI)

Location: Munich, Germany

Company

hirify.global develops software-defined, mass-scalable unmanned systems for defence and autonomous operations.

What you will do

• Design and build data pipelines from MES, ERP, operational, and back-office sources to feed machine learning models.
• Develop machine learning models for production and back-office use cases, from experimentation through production deployment.
• Deploy models with serving infrastructure, monitoring, drift detection, model versioning, and retraining workflows.
• Scope and validate machine learning use cases with the OAA Lead and cross-functional stakeholders, assessing feasibility, data availability, and ROI.
• Integrate model outputs into automated workflows with the Automation Engineer.
• Document and continuously improve data pipelines, model architectures, feature definitions, and deployment configurations.

Requirements

• 4–7 years of experience in data engineering or machine learning engineering.
• Professional experience deploying machine learning models to production, beyond research or notebook-level work.
• Strong Python and SQL skills for data engineering, machine learning development, extraction, validation, and pipeline development.
• Experience with scikit-learn, PyTorch, or equivalent machine learning frameworks.
• Understanding of MLOps fundamentals, including model serving, monitoring, versioning, and retraining.
• MSc in Data Science, Computer Science, Statistics, or an equivalent field.

Nice to have

• Experience with Airflow, dbt, or equivalent data pipeline tooling.
• Experience with AWS, GCP, Azure, or other cloud data platforms.
• Experience working with industrial, time-series, or back-office financial data.

Culture & Benefits

• Permanent, full-time employment.
• Individual contributor role with end-to-end ownership of complex, high-impact initiatives.
• Close collaboration with managers, team leads, the OAA Lead, Automation Engineering, and cross-functional stakeholders.
• Opportunity to shape operating processes and contribute to the development of autonomous defence systems.