Help solve some of the hardest applied machine learning problems in industrial inspection
Work on weld defect detection and corrosion analysis on radiographic data
Involvement in future UT-based systems and long-term corrosion prediction
Turn messy industrial data into reliable production systems
Managing external labeling teams
Training, evaluation, and experiment tracking workflows
Production inference pipelines
Support an exciting research project

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

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

Working Student, ML Engineer

Key skills