Eyüp Ülker - AI Engineer

About

AI Engineer with 2+ years of hands-on experience building production ML systems, scalable data infrastructure, and browser automation platforms. Architected distributed data collection networks on Kubernetes, developed real-time Detect & Avoid systems for autonomous drones, and engineered CDP-based skill systems turning web workflows into programmable APIs for AI agents. Physics background provides strong foundations in mathematical modeling and first-principles problem solving. Available for full-time roles starting June 2026.

Technical Skills

ML / AI

PyTorch TensorFlow OpenCV scikit-learn XGBoost Deep Learning Computer Vision Object Detection Image Segmentation Signal Processing

Infrastructure

Docker Kubernetes FastAPI GCP Cloud Run CI/CD MLOps Chrome DevTools Protocol Playwright Tor

Languages

Python TypeScript C++ SQL C# Go

Tools

NumPy pandas SciPy Git Postman Sphinx

Experience

AI Engineer — Olympos Sep 2025 – Present

Data infrastructure, browser automation, and ML-powered web intelligence platform

Architected distributed data collection infrastructure with Docker containers and rotating proxy networks, processing millions of records across multiple cloud nodes on GCP.
Engineered Chrome DevTools Protocol (CDP) skill system converting complex web workflows into programmable CLI APIs for AI agents — 100+ commands across 30+ skills powering a Claude Code plugin.
Built Android CDP skill: ADB-based CLI giving AI agents control over mobile devices — UI automation, app management, HTTPS interception via mitmproxy, and SSL unpinning with Frida.
Developed anti-detection solutions including TLS fingerprint impersonation, session management, and browser-routed API requests to handle WAF/CDN protections at scale.
Built investor probability models and founder classifiers using vector similarity search and decision tree ensembles for deal intelligence.

AI Engineer — SiFly (Internship) Apr 2025 – Jul 2025

Computer vision for autonomous drone systems

Developed real-time Detect and Avoid computer vision system for autonomous drones using PyTorch and OpenCV, enabling safe flight in complex airspace environments.

Machine Learning Engineer — Vitamu Jul 2023 – Nov 2024

End-to-end ML pipeline development for image analysis products

Built image preprocessing pipelines and trained segmentation models (U-Net variants) and classical ML classifiers, directly improving product accuracy and user experience.
Designed and implemented a weak labeling system that reduced manual annotation effort by ~60%, accelerating model iteration cycles from weeks to days.
Deployed models via CI/CD pipeline, managing the full lifecycle from training to production serving.
Documented APIs and codebases with Sphinx, cutting new developer onboarding time.

Junior AI Researcher — Earth-ML, Bogazici University Sep 2022 – Jan 2023

Deep learning research for geophysical data processing

Implemented ResNet and VAE architectures in PyTorch for denoising InSAR satellite imagery, improving signal-to-noise ratio for earthquake deformation analysis.
Applied signal processing techniques (Wavelet Transforms, STA/LTA, Template Matching) to seismological datasets, combining physics domain knowledge with ML methods.

Education

Bogazici University — B.Sc. Physics Sep 2019 – Jun 2026

Key coursework: Machine Learning Applications in Physics (Symbolic Regression, GNNs, RBMs), Machine Learning (SVM, CNN, NNs), Numerical Methods, Computer Vision, Computer Networking, Group Theory

Kadir Has University — Vocational Degree, Computer Programming Sep 2017 – Jun 2019

Key coursework: Operating Systems, Object-Oriented Programming (Java), Database Systems (SQL)

Certifications & Training

Quantum Optics 1 & 2 (Ecole Polytechnique) Qiskit Global Summer School 2022 Neural Networks and Deep Learning Structuring ML Projects