AI & Machine Learning Engineer
ElifCansuYıldız
Building production-ready LLM systems, agentic workflows, and dependable ML products.
About Me
I am an AI and machine learning engineer focused on production-ready LLM systems, retrieval-augmented generation, agentic workflows, and reliable ML products. I turn ambiguous requirements into practical solutions and take AI systems from data preparation and prototyping through evaluation, cloud deployment, and business validation.
My background spans enterprise AI, medical-imaging research, agricultural robotics, and distributed data systems. I hold an M.Sc. in Computer Science from the University of Bonn and a B.Eng. in Computer Engineering from Yıldız Technical University. Outside work, I have played competitive table tennis since the age of seven and also enjoy dancing and traveling.
Career constellation
The journey so far
Machine Learning Engineer
Haufe Akademie · Freiburg
Built production-ready enterprise RAG applications, LLM evaluation and monitoring pipelines, an AWS-deployed lead-conversion system, hybrid learning-content recommendations, and agentic market-research workflows.
Student Research Assistant
Fraunhofer IAIS · Bonn
Developed reproducible deep learning pipelines for medical image and video classification with PyTorch; evaluated state-of-the-art computer-vision models and automated experiment tracking for distributed training with Weights & Biases.
M.Sc. Computer Science
University of Bonn · Germany
Thesis: Improving Disease Detection with Deep Learning by Examining the Symmetrical Features of the Lungs.
Student Research Assistant
University of Bonn — Agricultural Robotics · Bonn
Implemented unsupervised ML methods to post-process Mask R-CNN outputs for improved soft-pepper detection, using Scikit-learn and PyTorch.
Research & Development Engineer
Link Bilgisayar · İstanbul
Developed a scalable resource management system over streaming Docker container statistics — real-time filtering with Spark SQL, producer-consumer with Kafka, storage on HDFS and MongoDB, analysis with Spark MLlib.
Intern R&D Engineer
Cybersoft · İstanbul
Built a data mining library for finance data on the Sparkling Water framework; benchmarking the distributed multi-node structure yielded up to 42% faster computation.
B.Eng. Computer Engineering
Yıldız Technical University · İstanbul
Thesis: Data Mining Library on the Sparkling Water Framework. The related work was presented at UBMK and published by IEEE.
Publication
Symmetry-aware Siamese Network: Exploiting Pathological Asymmetry for Chest X-Ray Analysis
Publication
Management of Virtualization Technologies with Complex Event Processing
Publication
On the RESTful Web Services for Managing Application Virtualization Environments
Publication
Data Mining Library for Big Data Processing Platforms: A Case Study - Sparkling Water Platform
Certificate
Deep Learning Specialization
Certificate
TensorFlow Developer Specialization
Toolbox
Skills
Selected work
Projects
Blog
Notebooks & write-ups
Hands-on implementations of classic ML and computer-vision techniques, written as annotated Jupyter notebooks.
Playing with HSV Color Space
This notebook covers how to mask color and change to another color using HSV color space which is an alternative color space to RGB where we can modify the colors by just shifting the hue of the image.
Jul 2022
Image Warping
Implementations of various image warping methods including fish eye, swirl, waves, cylinder anamorphosis, radial blur, bilinear warping, and perspective mapping effects.
Jun 2022
Edge Detection
Detecting edges using derivative of Gaussian kernels, and with Canny edge detector, taking the distance transform, hough transform, and applying mean shift algorithms to detect the edges more consistently.
Dec 2021
Basic Computer Vision Tasks
This notebook consists of calculation of integral image, mean grey value of the image, 2D filtering, generating a noisy image, denoising, separability of filters, Fourier transform on the images, and template matching.
Dec 2021
Support Vector Machines
Usage of SVM with different kernels on various datasets. SVM with linear kernels, polynomial kernels, RBF kernels, sigmoid kernels are run on datasets and results are shown.
Dec 2021
Segmentation with KMeans
Numpy implementation of k-Means on image data. k-Means algorithm has been run on an intensity image, RGB image, and properly scaled image position on an intensity image.
Dec 2021
Numerical Optimization
Numpy implementation of Gradient Descent, Gradient Descent with Line Searches, Gradient Descent using Conjugate Gradients, Newton's Method.
Dec 2021
Hopfield Networks
Numpy implementation of Hopfield Networks.
Dec 2021
Principal Component Analysis
Step-by-step implementation of Principal Component Analysis (PCA) Method.
Dec 2021Let's build something stellar.
Open to opportunities in AI engineering, production LLM systems, and machine learning. The fastest way to reach me is by email.
cansu96yildiz@gmail.comToolbox