Working Student ML Engineer

deeplify

80639 München
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Job Zusammenfassung

Du entwickelst Deep-Learning-Modelle für die industrielle Inspektion. Du kümmerst dich um Daten, Modelle und Infrastruktur, um zuverlässige Systeme zu schaffen.

Über den Job:

At deeplify, we’re building the first AI-native asset integrity co-pilot for critical industrial infrastructure. We turn inspection data from pipelines, chemical plants, ships, and bridges into real-time, risk-based maintenance decisions. We combine a digital inspection platform with proprietary deep-learning models and an evolving agentic AI system that learns from asset integrity engineers. This shifts asset integrity from slow, analogue, document-driven processes to a proactive, software-defined, and increasingly autonomous system.


TASKS

We are looking for an exceptional ML engineer working student to 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.


This is not a narrow research role. It is about solving hard end-to-end real-world problems: turning messy industrial data into reliable production systems.


  • 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

  • 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

  • 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

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Anfahrt zum Arbeitgeber

Job-ID.: 28931110

Zuletzt aktualisiert vor 1 Tag

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Technische ZeichnerIn, KonstrukteurIn
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