SME Engineer - Artificial Intelligence & Data Science (F/M/D)

TE Connectivity

Poland

On-site

PLN 318,471 - 403,396

Full time

14 days+

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Benefits offered by this job

Life insurance
Private medical healthcare package
Employee referral bonus
Multisport co‑financing
Performance-based bonus plans
Extensive training and career growth opportunities

Job summary

TE Connectivity in Szczecin, Poland, is offering a role that focuses on AI and Data Science in manufacturing. You will play a pivotal role in designing and deploying machine learning models that drive operational excellence across global manufacturing sites.

The position requires over 8 years of experience in AI with strong expertise in machine learning and familiarity with Industry 4.0 practices. TE Connectivity promotes a hybrid work model and provides extensive growth opportunities.

Qualifications

  • 8+ years of experience in AI, Data Science, or advanced analytics in manufacturing or industrial environments.
  • Experience delivering AI/ML solutions across multiple sites, regions, or global organizations.
  • Strong expertise in machine learning and deep learning techniques.

Responsibilities

  • Act as global SME for AI and Data Science across multiple manufacturing sites.
  • Design, build, validate, and deploy machine learning and AI models for industrial use cases.
  • Develop predictive and prescriptive analytics for quality, maintenance, yield, and supply chain optimization.

Skills

Machine learning
Deep learning
Statistical modeling
Python
SQL

Tools

TensorFlow
PyTorch
Scikit-learn
AWS
Azure
Power BI
Tableau

Job description

6/18/26

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.

Why you should join

You will play a key role in shaping how AI transforms global manufacturing operations across Europe, the Americas, and Asia. This is a rare opportunity to move beyond traditional data science and directly impact real industrial processes at scale. You will work at the intersection of advanced AI, smart factory systems, and business transformation, driving measurable operational excellence worldwide.

Your daily tasks
  • Act as global SME for AI and Data Science across multiple manufacturing sites
  • Design, build, validate, and deploy machine learning and AI models for industrial use cases
  • Identify and translate manufacturing challenges into scalable AI solutions with business stakeholders
  • Develop predictive and prescriptive analytics for quality, maintenance, yield, and supply chain optimization
  • Integrate AI models with MES, IIoT platforms, ERP systems, and smart factory ecosystems
  • Lead cross-regional AI projects and ensure successful deployment into production environments
  • Mentor plant teams and junior data scientists while promoting global AI best practices
Your ideal background
  • 8+ years of experience in AI, Data Science, or advanced analytics in manufacturing or industrial environments
  • Strong expertise in machine learning, deep learning, and statistical modeling techniques
  • Proven experience delivering AI/ML solutions across multiple sites, regions, or global organizations
  • Solid understanding of manufacturing processes (e.g., stamping, molding, assembly, plating)
  • Experience with Industry 4.0, smart factory, or digital manufacturing initiatives
  • Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
  • Experience working with cloud platforms (AWS or Azure) and data visualization tools (Power BI, Tableau)
Benefits
  • Collaborative and friendly work environment
  • Extensive training and career growth opportunities
  • Life insurance
  • Private medical healthcare package
  • Employee referral bonus
  • Multisport co‑financing
  • Performance-based bonus plans
Job Locations

PANATTONI PARK
SZCZECIN 1 KABLOWA, Zachodniopomorskie 70‑895
Poland

Posting City: SZCZECIN 1 KABLOWA

Job Country: Poland

Travel Required: 10% to 25%

Requisition ID: 154010

Workplace Type: Hybrid

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