R&D Engineer 'Applied Data Science - Computer Vision'

About:

Yapı Kredi Technology is a technology company that produces innovative, high quality, and high value-added products and solutions in the finance sector. With more than 2,000 employees, it aims to create products that will shape the sector for Yapı Kredi Bank and to be the undisputed leader in the field of technology by using modern architectural systems and cloud technologies. It also contributes to the development of new and exemplary products for the sector by using natural language processing, machine learning, artificial intelligence, and data mining technologies with its R&D team.

Who We Are:

At Yapı Kredi Technology, we research with passion, wonder as we learn, and implement innovations that shape the future together. We take responsibility from the first day with our expert colleagues and work with all our strength for pioneering applications. We make quick decisions and take action. We quickly adapt to innovations and changes.

What Do We Offer:

Opportunity to work in hybrid model

Opportunity to work in Koç Group Community Companies' offices

Chance to discover the natural wonders and amenities offered at Koç Topluluğu Spor Kulübü (KTSK)

Career development opportunities in a structured technology career path

Opportunity to benefit from BizClub and KoçAilem privileges exclusive to Yapı Kredi Technology employees

Company-contributed individual retirement insurance

Birthday off day

We are looking for an R&D Engineer to join the Computer Vision team within our Applied Data Science department. In this role, you will develop computer vision and document intelligence solutions that automate banking processes, strengthen fraud prevention, and improve operational efficiency.

You will work on problems such as OCR/ICR on banking documents, signature recognition and verification, object detection and segmentation, and multimodal document understanding with Vision-Language Models (VLMs).

As part of the Applied Data Science team, you will work closely with fast-paced and highly skilled R&D engineers, taking CV models from research and prototyping to production, and scaling and maintaining them in core banking systems.

Qualifications:

• M.Sc. or Ph.D. degree (completed, ongoing, or planned) in a Machine Learning / Deep Learning / Computer Vision related field from Computer, Industrial, or Electrical and Electronics Engineering,
• Demonstrated expertise in coding and problem-solving using Python,
• Hands-on experience with deep learning frameworks and model ecosystems, especially PyTorch and Hugging Face Transformers,
• Strong understanding of deep learning architectures for computer vision, including CNNs (e.g., ResNet) and Vision Transformers (ViT),
• Experience with object detection and segmentation models (e.g., YOLO family, Mask R-CNN, U-Net, or similar),
• Experience with OCR and ICR techniques and tools such as PaddleOCR, EasyOCR, or similar, including text detection and recognition on printed and handwritten documents,
• Experience with document layout analysis, table/form extraction, reading-order detection, and structured information extraction from scanned or digital documents.
• Proficiency in image processing with OpenCV (preprocessing, augmentation, geometric transformations, image enhancement),
• Familiarity with Vision-Language Models (VLMs) and multimodal approaches for document understanding and visual question answering,
• Interest or experience in signature recognition and verification, including handling limited and imbalanced data,
• Practical experience applying CV models to real-world datasets, with a demonstrated ability to analyze results, fine-tune models, and troubleshoot issues,
• Strong understanding of ML training, testing, validation, data labeling, and ML project pipelines,
• Experience with GPU-based training and distributed training setups,
• Experience with version control systems (Git, Git LFS),
• Experience with containerization using Docker,
• Experience with SQL databases (Oracle, PostgreSQL, SQL Server),
• Familiarity with Linux environments and command-line tools,
• Ability to communicate technical concepts and project updates effectively to stakeholders,
• Eager to follow technical literature and willing to contribute actively by publishing academic papers in international conferences.

Job Description:

• Design, develop, and train computer vision models for document intelligence, OCR/ICR, signature recognition, object detection, and segmentation use cases,
• Fine-tune and adapt pretrained models (CNNs, ResNet, ViT, YOLO, VLMs) to banking-specific data,
• Plan and manage data labeling processes, including defining annotation guidelines, preparing labeled datasets, and ensuring label quality and consistency,
• Build image preprocessing and data augmentation pipelines using OpenCV and PyTorch,
• Evaluate and benchmark OCR/ICR engines (PaddleOCR, EasyOCR, etc.) and VLM-based approaches for extracting information from banking documents,
• Take part in every phase of the project: data analysis, technical design, prototyping, model development, integration into core banking systems, and end-to-end testing,
• Optimize models for production performance, including latency, throughput, and resource usage,
• Monitor deployed models and continuously improve them based on performance metrics and business feedback,
• Follow state-of-the-art research in computer vision and multimodal AI and turn it into applicable solutions.

Would be Advantageous:

• Prior experience in banking, financial services, fraud detection, or document processing projects,
• Experience with model optimization and deployment tools (ONNX, TensorRT, OpenVINO, or similar),
• Experience with data annotation tools (CVAT, Label Studio, or similar),
• Experience with container orchestration tools (Kubernetes).

Candidate Selection Process:

Our recruitment process for all positions typically encompasses technical interviews, director assessments, competency evaluations, and personality tests. We will extend our offer to candidates who have successfully completed a positive evaluation process.

If you would like to get to know more about Yapı Kredi Technology, you can follow us!

https://www.ykteknoloji.com.tr

https://medium.com/yapi-kredi-teknoloji

6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında kişisel verilerinizin işlenmesinden doğan haklarınıza ve bu konudaki detaylı bilgiye https://kariyerim.yapikredi.com.tr/Account/StaticKvkk adresinde yer alan aydınlatma metnimizden ulaşabilirsiniz.