Ingénieur Intelligence Artificielle Site

Job profile & scope

Strategic Opportunity Identification

Collaborate closely with the different functions, lean teams and stakeholders to proactively identify and evaluate high-impact opportunities for AI/ML applications at site level.

Stakeholder Partnership

• Act as a key AI partner to cross-functional project teams, guiding them through the potentials and limitations of AI/ML to effectively address specific business challenges.
• Translate business challenges into clear problem statements, measurable success criteria, and value hypothesis.

AMP 2.0 Ambassador

• Key partner for the site to leverage the AMP 2.0 possibilities.
• Coach the different teams in AMP 2.0 and guide them through the different functionalities to develop own use-cases in AMP.

Feasibility studies and proof-of-concept deployment

Drive the proof-of concept (POC) development for high-impact opportunities at site level and in close cooperation with the PT Central AI team, to quickly run feasibility tests or adapt existing use-cases for the site business needs.

Scaling

Partner with the PT central AI team and other stakeholders to scale AI POC to production scale deployments and activate the business impact of the AI solution at site level.

Soft skills

• Domain Knowledge: Good understanding of our products & processes
• Collaborative Team Player: Ability to work effectively and collaboratively within diverse, cross-functional teams at site and PT level
• Communication & Presentation: Good communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and prepare clear, concise documentation
• Problem-Solving & Critical Thinking: Strong analytical and problem-solving skills, with a proactive approach to identifying and resolving technical challenges
• Project Leadership: Good understanding of project management principles, including agile methodologies, to drive projects from concept to completion

Qualifications

Applied AI/ML skill set

• Hands-on experience applying AI/ML to operations (e.g., data analysis, time-series forecasting and anomaly detection, computer vision for quality/inspection, optimization, and basic NLP/LLM use cases).
• Proficiency with Python and data analysis methodologies; practical experience with data collection, feature engineering, model evaluation, and experimental POC design.
• Fluency in French and English
• Master’s degree in Computer Science, Digital Innovation, Big Data, AI, or Industry 4.0

Additional Information

Relocation Assistance Provided: No