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Working Student – ML Engineer
deeplify GmbHWorking Student ML Engineer solving hard applied machine learning problems in industrial inspection. Building end-to-end ML systems and supporting research projects with real-world impact.
About the role
Key responsibilities & impact- Help us solve some of the hardest applied machine learning problems in industrial inspection — from weld defect detection and corrosion analysis on radiographic data to future UT-based systems and long-term corrosion prediction
- Deep learning models for weld defect detection and corrosion analysis on radiographic and ultrasonic data
- Managing external labeling teams
- Training, evaluation, and experiment tracking workflows
- Production inference pipelines
- Support an exciting research project
Requirements
What you’ll need- Strong hands-on ML engineering skills
- High ownership : you take responsibility, drive things forward, and do not wait to be told every next step
- High urgency : you move fast, care about execution, and know how to create momentum
- Excited by messy, difficult, real-world problems with no obvious solution
- Comfortable working across data, models, infrastructure, and deployment
- Bonus: experience in computer vision, MLOps, production ML, imaging, or sensor data
Benefits
Comp & perks- Work on technically ambitious problems with real industrial impact
- Build end-to-end ML systems, not just models in isolation
- Help lay the foundation for a scalable internal ML platform
- Be part of a team tackling long-term challenges like corrosion prediction, a genuinely hard problem with significant upside
- Well above average working student compensation
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdeep learningweld defect detectioncorrosion analysisradiographic dataultrasonic dataproduction inference pipelinesMLOpscomputer visionimaging
Soft Skills
high ownershiphigh urgencyproblem-solvingresponsibilityexecutioncreating momentumadaptabilitycollaborationcommunicationinitiative