Vision Engineer

Selecta sas; Vicenza; In loco; EUR 40.000 - 60.000; Tempo pieno

Descrizione del lavoro

A leading manufacturing company is seeking a Vision Engineer to manage engineering operations at its Pisa plant. The ideal candidate will have experience in deep learning and computer vision, focusing on optimizing processes in a pharmaceutical environment. Essential qualifications include a Master's degree or PhD and strong technical proficiency in relevant tools. The role offers a dynamic environment and opportunities for growth.

Servizi

Health Care Insurance

Employee Stock Purchase Plan

Wellness Programs

Training on technical skills

Competenze

• 1-3+ years experience in a pharmaceutical company with a focus on computer vision, deep learning, or inspection systems.
• Good knowledge of cGMPs and pharma/HSE rules and standards.
• Hands-on experience with data pipelines for large-scale image processing.

Mansioni

• Manage engineering operations for manufacturing operations in Pisa plant.
• Design and optimize deep learning models using frameworks.
• Promote continuous improvement of processes and equipment.

Conoscenze

Deep technical proficiency on pharmaceutical systems and equipment

Fluent in English

Exceptional ability to manage simultaneous activities

Leadership and influence

Strong understanding of GPU‑based acceleration using NVIDIA CUDA

Creative capacity for developing new ways to do things better

Formazione

Master’s degree or PhD in Computer Engineering, Automation, Electronics, or a related field

Strumenti

MATLAB

Python

C++

PyTorch

TensorFlow

OpenCV

Halcon

Descrizione del lavoro

Job Title

Vision Engineer

Join us in making a difference.

Location

Pisa

Eligibility

Previa verifica dei requisiti professionali, costituisce titolo preferenziale l'appartenenza alle Categorie Protette ai sensi dell'art 1 L. ***** e/o alle categorie di lavoratori che risultino percettori di interventi a sostegno del reddito e/o risultino disoccupati a seguito di procedure di licenziamento collettivo.

About the role

Manage engineering operations for manufacturing operations in Pisa plant. Provide holistic engineering and maintenance support to the site to sustainably achieve capacity plans and fulfillment targets. Define maintenance activities for process equipment, providing engineering technical support and capital planning and execution. Manage deviations, elaborate and update SOPs related to process equipment failure.

Accountabilities

• Design and optimize deep learning models using frameworks such as PyTorch and TensorFlow.
• Leverage architectures like Faster R-CNN, YOLO, and novel state‑of‑the‑art algorithms to detect defects and classify images with high accuracy.
• Develop innovative loss functions and methodologies to enhance model robustness and performance.
• Serve as an expert and the focal point for technical discussions regarding equipment/processes/systems.
• Manage deviations and changes according to GMP rules.
• Propose and evaluate with functional leader new ideas or projects, formulating precise business cases and assessing costs and resources.
• Make alterations and adjustments to processes/equipment.
• Draft/review qualification documents, evaluations technical Standard Operating Procedures (SOPs), and instructions.
• Manage technical records and diagrams.
• Manage relationships with technical third parties such as equipment suppliers, directly handling service requests and agreements.
• Promote and lead the exchange of technical knowledge within and outside the site.
• Implement and fine‑tune AVI systems for real‑time quality inspection on automated production lines.
• Be accountable for HSE topics and investigations in the area under the employee’s control.
• Provide strategic oversight and act as an advisor or trainer to maintenance and production members.
• Conduct investigations and coordinate the resolution of problems and root‑cause analysis (RCA).
• Promote continuous improvement of processes and equipment, ensuring alignment with the latest internal and external rules and regulations.
• Execute projects within challenging timelines and environments.

Education, Behavioral Competencies and Skills

• Master’s degree or PhD in Computer Engineering, Automation, Electronics, or a related field.
• 1‑3+ years experience in a pharmaceutical company or related industry with a specific focus on computer vision, deep learning or inspection systems.
• Deep technical proficiency on pharmaceutical systems and equipment.
• Good knowledge of cGMPs and pharma/HSE rules and standards.
• Fluent in English.
• Proficiency in MATLAB, Python, and C++ for algorithm development and system integration.
• Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow) and computer vision libraries (e.g., OpenCV, Halcon).
• Experience with modern architectures such as Faster R-CNN, YOLO, and EfficientDet for image analysis and defect detection.
• Strong understanding of GPU‑based acceleration using NVIDIA CUDA for optimizing training and inference workflows.
• Hands‑on experience with data pipelines and tools for large‑scale image processing.
• Exceptional ability to manage simultaneous activities, competing priorities, and challenges.
• Leadership and influence.
• In‑depth knowledge of sterile production processes and equipment.
• Strong ability to work and communicate effectively with the team and peers within a manufacturing and engineering organization.
• Excellent communication skills: written and verbal.
• Prioritization and project‑management skills.
• High‑level problem‑solving/root‑cause investigation skills.
• Creative capacity for developing new ways to do things better, cheaper, faster.

What you bring to Takeda

• Tech‑savvy individuals who thrive in a dynamic manufacturing environment.

What Takeda can offer you

• Health and Finance
  • Health Care Insurance
  • Employee Stock Purchase Plan
  • Employee discount programs at various businesses, stores, and medical services
• Training and Development
  • Training on technical skills and professional development
  • Job Rotation programs to work in different departments
  • Employee‑led groups focused on raising awareness of Diversity, Equity, and Inclusion and engaging in community outreach
• Values‑Based Culture
  • Wellness Programs
  • On‑site cafeteria and coffee bar
  • Resources for mental, physical, financial, and spiritual health
  • Parental Leave

Other Information

• Locations: ITA – Pisa
• Worker Type: Employee
• Worker Sub‑Type: Regular
• Time Type: Full time