Vision Engineer

at  Takeda Pharmaceutical

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JOB DESCRIPTION

Sarà considerato requisito preferenziale l’appartenenza alle categorie protette (legge n. 68/99)
Present in Italy since 1982, Takeda has two plasma-derived drug production sites in Rieti and Pisa, supporting patients with rare and complex diseases. These sites focus on the production of therapies derived from immunoglobulins, albumin, and coagulation factors. As partners of the National Health System, we transform plasma into life-saving drugs under the “National Self-Sufficiency of Blood and its Products” program. We supply high-quality medicines worldwide, with a strong presence in Europe, America, and Asia.
Takeda Manufacturing Italia SpA has been awarded the Top Employer certificate for several years and is committed to inclusion, career growth, and sustainability. Join us in making a difference.

ACCOUNTABILITIES:

• Design and optimize deep learning models using frameworks such as PyTorch and TensorFlow.
• Leverage architectures like Faster R-CNN, YOLO, and novels state -of-art algorithms to detect defects and classify images with high accuracy.
• Develop innovative loss functions and methodologies to enhance model robustness and performance.

EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:

• Master’s degree or PhD in Computer Engineering, Automation, Electronics, or a related field.
• 1-3+ years experience in pharmaceutical Company or related industries with specific focus on computer vision, deep learning or inspection systems.
• In depth 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 / influence
• In-depth knowledge of the sterile production process and equipment
• Strong ability to work and communicate effectively with the team and peers within a manufacturing and engineering organization. This includes excellent communication skills: written and verbal
• Prioritization & project management skills
• High-level problem-solving / root cause investigation skills
• Creative capacity for developing new ways to do things better, cheaper, faster

OBJECTIVES/PURPOSE:

• 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.

CORE ELEMENTS RELATED TO THIS ROLE:

• Design and optimize deep learning models using frameworks such as PyTorch and TensorFlow.
• Leverage architectures like Faster R-CNN, YOLO, and novels state -of-art algorithms to detect defects and classify images with high accuracy.
• Develop innovative loss functions and methodologies to enhance model robustness and performance.
• Serves as an expert and the focal point for technical discussions regarding equipment/processes/systems.
• Manages deviations and changes according to GMP rules.
• Proposes and evaluates with functional leader new ideas or projects, formulating precise business cases and assessing costs and resources.
• Makes alterations and adjustments to processes/equipment.
• Drafts/reviews qualification documents, evaluations, technical Standard Operating Procedures (SOPs), and instructions.