Master Thesis: Product Image Analytics Enablement for Manufacturing Quality Inspection
A Snapshot of Your Task
Advanced manufacturing technologies such as CT scanning and 3D printing generate large volumes of image data that can provide valuable quality insights. However, there is currently no end-to-end solution for ingesting, analyzing, and deploying image analytics models across manufacturing processes.
In this thesis, you will support the development of a scalable image analytics framework for industrial quality inspection. The focus will be on image data ingestion, AI/ML-based analytics, and the deployment of custom models (Bring Your Own Model - BYOM) to enable automated quality assessment and defect detection.
How You'll Make an Impact
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Analyze industrial image datasets (CT scans, layered images, 3D-print images).
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Design and develop image ingestion and preprocessing workflows.
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Explore and implement AI/ML models for quality inspection and defect detection.
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Validate model performance using manufacturing quality criteria.
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Investigate BYOM deployment approaches and end-to-end analytics pipelines.
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Document findings and present recommendations to business stakeholders.
What You Bring
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Master's studies in Data Science, AI, Computer Science, Engineering, or a related field.
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Passion for machine learning and image analytics.
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Willingness to learn and adapt to new technologies and methodologies.
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Experience with data preparation and engineering, preferably in Python or similar programming languages.
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Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch), version control (Git), cloud environment (AWS & CDK) is a plus.
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Self-driven with a problem-solving mindset to achieve project goals.
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Enthusiasm for working alongside experienced professionals in a collaborative environment.
About the Team
You will join Siemens Energy's Quality Inspection Technology and Digitalization community, working alongside engineers and data scientists on innovative solutions that improve manufacturing quality through AI and advanced analytics.
Expected Outcome
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Assessment of industrial image data sources.
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Prototype image ingestion and analytics pipeline.
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AI/ML models for image-based quality inspection.
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Validation results and deployment recommendations.
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Foundation for scalable industrial image analytics within Siemens Energy.
Who is Siemens Energy?
At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo
Our Commitment to Diversity
Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.
Application
Don’t hesitate – apply via https://siemensenergy.avature.net/internalcareers , id nr 306480 not later than 2026-11-23.
Ongoing selection is applied, the role might be filled before last application date.
Trade Union Representatives:
Unionen, [email protected]
Sveriges Ingenjörer & SACO, [email protected]
Ledarna, Anders Fors, [email protected]
IF Metall, Mikael Malmgren, [email protected]
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