Forvia, a sustainable mobility technology leader

We pioneer technology for mobility experience that matter to people.

Within the Product Line Engineering Advanced Manufacturing Engineering organization, the VIE Data, Digital & Artificial Intelligence Engineer will support the deployment of Artificial Intelligence (AI), Data Analytics, and Digital Manufacturing solutions aimed at improving industrial processes, manufacturing performance, and process control across Forvia production plants worldwide.

The role contributes directly to Forvia's industrial transformation roadmap by leveraging industrial data, machine learning, computer vision, and digital technologies to optimize manufacturing equipment, process parameters, product quality, and operational efficiency.

Based in Hannover, Germany, the engineer will join a global team of 13 manufacturing experts and engineers, supported by two students. The team is responsible for developing and maintaining global manufacturing standards for Welding, Forming, Assembly, and Surface Treatment processes, as well as defining standard equipment deployed across Forvia plants worldwide.

The Hannover engineering centre operates in a highly international and multicultural environment. English is the primary language for meetings, technical discussions, and daily communication.

Your mission, roles and responsibilities

The main missions of the role are:

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.

Your profile and competencies to succeed

Qualifications

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.

What we can do for you

• You will work within an international team full of energy;
• You will work on challenges that matter;
• You will find a strong emphasis on talent development and abundant opportunities for growth;
• You will have the autonomy to launch processes and to be accountable for them as a process owner;
• A powerful VIE community spirit within Forvians.

Why join us

FORVIA, a global automotive technology supplier, comprises the complementary technology and industrial strengths of Faurecia and HELLA.

With over 137 500 people, including more than 12,000 R&D engineers across 40+ countries, FORVIA provides a unique and comprehensive approach to the automotive challenges of today and tomorrow. Composed of 6 business groups and a strong IP portfolio of over 12,400 patents, FORVIA is focused on becoming the preferred innovation and integration partner for OEMs worldwide.

In 2025, the Group achieved a consolidated revenue of 26.2 billion euros prior to IFRS 5. FORVIA SE is listed on the Euronext Paris market under the FRVIA mnemonic code and is a component of the SBF 120 index.

FORVIA aims to be a change maker committed to foreseeing and making the mobility transformation happen. www.forvia.com