Pflichtpraktikum Data Engineering & Data Analytics im Akustik-Testing
Core
Develop and optimize machine learning models for the precise analysis of acoustic measurement signals to drive digitalization in testing.
Role type
Intern, Machine Learning Engineer (Acoustics)
Builds
Cloud-based data evaluation pipelines and acoustic analysis models
Domain
Automotive acoustics, data engineering, machine learning
Deliverable
production ML models
Required skills
Python programming, machine learning model training, cloud data processing
Preferred skills
Databricks experience, technical background in mechatronics/electrical engineering/mechanical engineering/data science/physics
Responsibilities
Design, train, and improve ML models for acoustic signal analysis; optimize data evaluation possibilities in the cloud; collaborate with teams on the interface of testing and data processing.
Seniority
Intern
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