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Job Overview
TE Connectivity’s Engineering Project Management Teams manage cross functional engineering projects. They work with Product Management, Sales, Quality, Manufacturing, Finance, and other functions across TE to assure projects meet financial, schedule and customer expectations. They are responsible for defining and creating project schedules, portfolio management, communication and execution of programs, identifying resource constraints and working with management for resolution, while adhering to LeanPD processes.
We are seeking an experienced and innovative Principal AI Projects professional to lead our advanced AI initiatives in the field of injection molding.
The ideal candidate will possess a deep understanding of both AI technologies and injection molding processes, enabling them to drive the development and implementation of AI solutions that enhance efficiency, quality, and innovation in our manufacturing operations.
Key Responsibilities
Leadership and Strategy:
1. Lead the AI projects, providing strategic direction and technical expertise.
2. Develop and implement a roadmap for AI integration in injection molding processes.
3. Collaborate with senior management to align AI initiatives with overall business objectives.
AI Development and Implementation:
4. First steps in how to Design, develop, and deploy AI models to optimize injection molding processes, including predictive maintenance, quality control, and process optimization.
5. First steps in how to Implement machine learning algorithms to analyze production data and identify patterns for process improvement.
6. Understanding how to connect and integrate AI solutions with existing manufacturing systems and workflows.
Project Management:
7. Experience to Manage multiple projects simultaneously, ensuring timely delivery and alignment with project goals.
8. Coordinate with cross-functional teams including engineering, production, and IT to ensure successful project execution.
9. Monitor project progress, identify potential risks, and implement mitigation strategies.
Research and Innovation:
10. Stay updated with the latest advancements in AI and machine learning technologies.
11. Drive innovation by researching and recommending new AI technologies and methodologies applicable to injection molding.
12. Foster a culture of continuous improvement and innovation within the team.
Data Management:
13. Oversee the collection, storage, and analysis of large datasets from injection molding processes.
14. Ensure data integrity and security while enabling data-driven decision-making.
15. Develop and maintain documentation for best practices.
Training and Support:
16. Provide training and support to team members and other stakeholders on AI tools and methodologies.
17. Conduct workshops and collaborate with the Global COI AI to promote AI literacy and adoption within the organization.
18. Mentor and multiplicator to internally to share AI knowledge to engineers and data scientists.
What your background should look like:
Education:
19. Master’s degree in Computer Science, Engineering, Manufacturing, Data Science, or a related field.
Experience:
20. 2-5 years of experience in Data science, AI and machine learning.
21. At least 5 years of experience in the manufacturing sector, preferably in injection molding.
22. Proven track record of leading and delivering successful AI projects.
Technical Skills:
23. Strong proficiency in programming languages such as Python, R, or Java.
24. Experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
25. Knowledge of injection molding processes and related manufacturing technologies.
26. Familiarity with data analytics tools and platforms (e.g., SQL, Hadoop, Spark).
Soft Skills:
27. Excellent leadership and team management skills.
28. Strong problem-solving and analytical abilities.
29. Effective communication and presentation skills.
30. Ability to work collaboratively in a cross-functional team environment.
Preferred Qualifications:
31. Experience with Industry 4.0 technologies and IoT integration in manufacturing.
32. Knowledge of statistical process control (SPC) and Six Sigma methodologies.
33. Previous experience in a principal or senior role in AI/ML projects.
Competencies
Managing and Measuring WorkBuilding Effective TeamsMotivating OthersValues: Integrity, Accountability, Inclusion, Innovation, TeamworkSET : Strategy, Execution, Talent (for managers)