Job

Data & Machine Learning Engineer (All genders)

Stark · Munich

At a glance

Type: Job
Organisation: Stark
Location: Munich
Work mode: On-site
Deadline: Rolling / not stated
Posted: 21 Aug 2026

About this job

About UsSTARK is a new kind of defence technology company revolutionising the way autonomous systems are deployed across multiple domains. We design, develop, and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective — providing operators with a decisive edge in contested environments.We are focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe, today. About the teamThe 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. Your missionAs 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. Responsibilities<ul><li style="font-style:italic;">Design and build data pipelines from operational (MES, ERP) and back-office sources feeding ML models</li><li style="font-style:italic;">Develop ML models for production and back-office use cases — from experimentation through to production deployment</li><li style="font-style:italic;">Deploy models into production: serving infrastructure, monitoring, drift detection, and retraining workflows</li><li style="font-style:italic;">Work with the OAA Lead and stakeholders to scope and validate ML use cases — feasibility, data availability, ROI</li><li style="font-style:italic;">Collaborate with the Automation Engineer to integrate model outputs into automated workflows</li><li style="font-style:italic;">Maintain and improve deployed models as data distributions and operational conditions evolve</li><li style="font-style:italic;">Document data pipelines, model architectures, feature definitions, and deployment configurations</li></ul> Qualifications<ul><li style="font-style:italic;">4–7 years in data engineering or ML engineering</li><li style="font-style:italic;">Demonstrated experience deploying ML models to production: not just research or notebook-level work</li><li style="font-style:italic;">Python: core language for data engineering and ML development</li><li style="font-style:italic;">SQL: data extraction, validation, and pipeline development</li><li style="font-style:italic;">ML frameworks: scikit-learn, PyTorch, or equivalent</li><li style="font-style:italic;">MLOps fundamentals: model versioning, serving, monitoring, retraining</li><li style="font-style:italic;">MSc in Data Science, Computer Science, Statistics, or equivalent</li></ul> Nice to have<ul><li style="font-style:italic;">Data pipeline tooling: Airflow, dbt, or equivalent</li><li style="font-style:italic;">Cloud data platforms: AWS, GCP, or Azure</li><li style="font-style:italic;">Experience with industrial, time-series, or back-office financial data</li></ul>Find <a href="https://www.arbeitnow.com">Jobs in Germany</a> on Arbeitnow</a>

How to apply

1 Read the full details above and confirm you meet the eligibility criteria.
2 Prepare your documents — an updated CV, and any cover letter, proposal or certificates required.
3 Click Apply on official site to complete your application on Stark’s official page.
4 Submit as early as possible — many close once filled.

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Frequently asked questions

How do I apply for Data & Machine Learning Engineer (All genders)?

Review the full details and eligibility on this page, prepare your documents, then use the “Apply on official site” button to complete your application on Stark’s official page.

Is this opportunity remote or location-based?

This opportunity is based in Munich. Check the official listing for any relocation or on-site requirements.

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