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описание
At Stark, we forge the future of European and national security through cutting-edge, AI-driven technology and unmatched engineering precision. As a premier defence technology company, our mission is clear: to equip NATO Allies and their partners with next-generation autonomous defence platforms and advanced AI-driven software built to perform in the world’s most demanding environments.
We believe that true security stems from relentless innovation. By combining elite engineering talent with agile technology and an AI-native operational culture, Stark turns complex defence challenges into field-tested, multi-domain solutions.
задачи
As Data & Machine Learning Engineer, you own the data infrastructure and ML model development for the OAA team's AI use cases. You build the pipelines that feed models with clean, reliable data from both operational systems and back-office sources, deploy models into production, and ensure they perform reliably — from yield prediction on the line to anomaly detection in financial data.
Design and build data pipelines from operational (MES, ERP) and back-office sources feeding ML models
Develop ML models for production and back-office use cases — from experimentation through to production deployment
Deploy models into production: serving infrastructure, monitoring, drift detection, and retraining workflows
Work with the OAA Lead and stakeholders to scope and validate ML use cases — feasibility, data availability, ROI
Collaborate with the Automation Engineer to integrate model outputs into automated workflows
Maintain and improve deployed models as data distributions and operational conditions evolve
Document data pipelines, model architectures, feature definitions, and deployment configurations
требования
4–7 years in data engineering or ML engineering
Demonstrated experience deploying ML models to production: not just research or notebook-level work
Python: core language for data engineering and ML development
SQL: data extraction, validation, and pipeline development
ML frameworks: scikit-learn, PyTorch, or equivalent
MLOps fundamentals: model versioning, serving, monitoring, retraining
MSc in Data Science, Computer Science, Statistics, or equivalent
Data pipeline tooling: Airflow, dbt, or equivalent
Cloud data platforms: AWS, GCP, or Azure
Experience with industrial, time-series, or back-office financial data
If you're interested in building the future of European Defence with us, and you see yourself reflected on the description above, please send us your CV in English. We're looking forward to meeting you!
SECURITY CLEARANCE
Due to the nature of our work in the defence sector, candidates must be eligible to obtain and maintain the appropriate security clearance required for this position. Details will be provided during the recruitment process.
условия
The software and systems you work on directly protect personnel and defend European and national sovereignty.
You will work alongside industry-leading minds on autonomous systems, advanced propulsion, and secure cyber platforms.
We foster a fast-paced, collaborative environment where bold ideas are supported by serious R&D backing.
The Operations Excellence team sits within the COO organization and serves as a strategic partner to managers, team leads, and colleagues across Stark. By delivering data-driven insights, leading critical projects, and driving continuous process improvement, we help the organization operate more efficiently, scale effectively, and achieve its goals faster.
As an individual contributor, you will take end-to-end ownership of complex initiatives with significant business impact. Working closely with cross-functional stakeholders, you will have the opportunity to influence key decisions, shape core operating processes, and contribute directly to the success of one of Europe’s fastest-growing unicorns.