Vehicle Noise Testing & Machine Learning Engineer, Trainee

Description

This is a trainee role in the NVH (Noise, Vibration & Harshness) team of a global automotive company, combining machine learning, AI and vehicle test work.

The team wants a self-driven, curious intern who wants to apply technical skills to real engineering problems.

Responsibilities

• Help build a predictive model that estimates tyre noise from test inputs such as tyre pressure, tyre stiffness, vehicle speed, ambient temperature and other vehicle and test conditions.
• Improve the team's internal RAG application by adding technical parameters drawn from historical vehicle development data.
• Analyse and process vehicle test data.
• Develop predictive models that estimate how tyres behave in terms of noise.
• Study how tyre and vehicle parameters affect exterior noise.
• Create a user-friendly interface that lets engineers simulate tyre noise for different tyre specifications and operating conditions.
• Support the digitalisation and improvement of NVH engineering processes.

Requirements

• Good working knowledge of machine learning and AI concepts and tools.
• Programming skills in Python or a similar language.
• A solid grasp of mathematical modelling and data analysis methods.
• Genuine interest in using technology on real engineering problems.
• Fluent English, both spoken and written.

Conditions

Based in Barcelona, Spain.

Hybrid working: a mix of remote work and on-site collaboration at NTCE facilities.

You must be enrolled in a Bachelor's or Master's degree and able to sign a university internship agreement with your institution.

The company values differences among people and aims to build inclusive teams.

Benefits

• Hands-on work with automotive technology.
• A real project that directly influences vehicle development.
• Work alongside colleagues from many countries.
• Paid compensation during the internship.
• Suitable for students completing a Bachelor's Final Project or a Master's Thesis.