VIE - Data, Digital & AI- Frames Advanced Manufacturing Engineering (m/w/d), HAnnover

As a leader in sustainable mobility technologies, we aim to have a positive impact on society and the planet. With a presence in over 40 countries and teams comprising people of more than 140 nationalities, FORVIA is a truly international company, with diversity at the very heart of its DNA. Committed to safeguarding the future of our planet and future generations, we conduct all our operations through the lens of sustainable development.

Mission

1. Manufacturing Process Data & Analytics

• Collect, structure, and analyse manufacturing process data from industrial equipment, sensors, and connected production systems.
• Support the implementation and utilization of industrial data platforms, data lakes, and manufacturing data models.
• Develop dashboards, reports, and KPIs to monitor equipment performance, process capability, operational efficiency, and production quality.
• Ensure data quality, consistency, traceability, and accessibility for digital manufacturing and AI applications.
• Contribute to data-driven decision-making by identifying trends, process deviations, and improvement opportunities.

2. AI for Quality & Process Monitoring (Laser Welding, MAG Welding, and Noise Control Applications)

• Quality & Process Monitoring
• Develop and implement data-driven methods to detect process drifts and abnormal equipment behaviour.
• Design and deploy anomaly detection algorithms for manufacturing operations.
• Support the training, validation, and continuous improvement of machine learning models.
• Analyse manufacturing data to identify root causes of quality issues and process variability.
• Contribute to predictive maintenance and process control initiatives.
• Computer Vision and Intelligent Positioning
• Support the development of camera-based inspection and positioning systems used in automated manufacturing and assembly operations.
• Develop AI-assisted vision solutions to improve component detection, positioning accuracy, and adaptive machine adjustment.
• Participate in the evaluation and testing of computer vision technologies for industrial applications.
• Contribute to reducing assembly defects, scrap, and rework through intelligent automation solutions.
• Collaborate with equipment suppliers and plant engineering teams during proof-of-concept and deployment activities

3. AI for Forming and Stamping Applications (optional)

Depending on project priorities and candidate interests, the engineer may also contribute to AI-driven solutions for metal forming and stamping processes, including:

• Process parameter optimization using machine learning techniques.
• Predictive quality models for forming operations.
• Detection and classification of defects using advanced analytics and computer vision.
• Development of digital twins and simulation-based optimization approaches.
• Statistical analysis of production and tooling performance data.

Profile

The ideal candidate will have/be:

Minimum education level: Master Degree (Engineering School or University)
Specialization in:

• Data Science / Computer Science / Artificial Intelligence / Machine Learning
• Manufacturing Engineering / Industrial Engineering

Experience :

• First experience through projects, internships or academic research in AI, Data Analytics or Industrial Engineering appreciated.
• Knowledge of manufacturing processes (Assembly, Metal Welding, Metal Forming is a plus.

Skills and competencies:

• Technical Skills
• Machine Learning and Artificial Intelligence fundamentals.
• Data Analytics and statistical methods.
• Python programming.
• SQL and database management.
• Manufacturing data architectures and cloud technologies.
• Computer Vision fundamentals..

Soft Skills

• Strong analytical and problem-solving mindset.
• Curiosity and innovation mindset.
• Ability to work in an international and multicultural environment.
• Autonomous and proactive attitude.
• Good communication and presentation skills.
• Team spirit and collaboration orientation.

Languages

• English: Fluent (mandatory/ C1 level mini / TOEIC > 800)
• French: Appreciated
• Additional languages are a plus.