14+
Years Experience
6+
Years at Apple
639
Citations
10
h‑index
20+
Publications
Ph.D.
EE Engineering
Machine Learning Engineer at Apple with a Ph.D. and a background rooted in neural architecture
design and optimization theory — from novel network architectures during M.Sc. and Ph.D. to
foundation model fine-tuning, posttraining, and multimodal system evaluation at scale in production.
Experience
Machine Learning Engineer
2019 – Present
2019 – Present
Apple Inc. · Cupertino, USA
- Built a scalable multi-step synthetic data generation pipeline using parameterized prompting to produce structured, criteria-driven training data for multimodal model development.
- Part of the core team shipping NLP model features to production — spanning model training, offline/online evaluation setup, and deployment.
- Drove end-to-end ML delivery of intelligent assistant features localized across 36 languages, coordinating cross-functional teams and presenting outcomes to leadership.
- Fine-tuned large-scale multimodal (visual) foundation models using purpose-built synthetic training data, enabling visual understanding capabilities for intelligent assistant applications.
- Designed end-to-end and component-level evaluation pipelines; identified coverage gaps and proposed an Evaluation Quality Metrics framework adopted cross-functionally.
- Key contributor to ReALM (SIGDIAL 2024), MARRS (CRAC 2023), and LVSum (arXiv 2026).
Assistant Professor Dr.
2016 – 2019
2016 – 2019
Çukurova University · Adana, Turkey
- Led research in deep learning & neural architectures.
- Collaborated with Berkeley Lab – ESNET (Dr. Mariam Kiran).
- Supervised 4 M.Sc. theses; co-headed department.
Research Assistant
2012 – 2015
2012 – 2015
Adana Alparslan Türkeş S&T University · Turkey
Selected Publications
•
Sarigul M., Ozyildirim B.M., Avci M. “Differential convolutional neural network.” Neural Networks, 2019. 219 citations
Sarigul M., Ozyildirim B.M., Avci M. “Differential convolutional neural network.” Neural Networks, 2019. 219 citations
•
Ozyildirim B.M., Avci M. “Generalized classifier neural network.” Neural Networks, 2013. 96 citations
Ozyildirim B.M., Avci M. “Generalized classifier neural network.” Neural Networks, 2013. 96 citations
•
Kiran M., Ozyildirim M. “Hyperparameter tuning for deep RL applications.” arXiv, 2022. 68 citations
Kiran M., Ozyildirim M. “Hyperparameter tuning for deep RL applications.” arXiv, 2022. 68 citations
•
Ozyildirim B.M., Kiran M. “Levenberg–Marquardt multi-classification using hinge loss.” Neural Networks, 2021. 50 citations
Ozyildirim B.M., Kiran M. “Levenberg–Marquardt multi-classification using hinge loss.” Neural Networks, 2021. 50 citations
•
Moniz J.R.A., Krishnan S., Ozyildirim B.M., et al. “ReALM: Reference Resolution as Language Modeling.” SIGDIAL, 2024. 10 citations
Moniz J.R.A., Krishnan S., Ozyildirim B.M., et al. “ReALM: Reference Resolution as Language Modeling.” SIGDIAL, 2024. 10 citations
•
Patel A., Ozyildirim M., et al. “LVSum: Timestamp-Aware Long Video Summarization.” arXiv, 2026.
Patel A., Ozyildirim M., et al. “LVSum: Timestamp-Aware Long Video Summarization.” arXiv, 2026.
Technical Skills
Languages / Libraries
C, Python, PyTorch, OpenCV, Pandas
C, Python, PyTorch, OpenCV, Pandas
Deep Learning
CNNs · Deep Generative Models · Deep Reinforcement Learning
CNNs · Deep Generative Models · Deep Reinforcement Learning
LLM / Inference
Finetuning · Posttraining · Inference optimization (MLX, vLLM)
Finetuning · Posttraining · Inference optimization (MLX, vLLM)
Multimodal & Vision
Video understanding & summarization · Object Detection · Multimodal evaluation pipelines
Video understanding & summarization · Object Detection · Multimodal evaluation pipelines
Data Engineering
Synthetic data generation · Structured, Unstructured, Time-Series & Video/Image pipelines
Synthetic data generation · Structured, Unstructured, Time-Series & Video/Image pipelines
Research
Neural architecture design · Optimization methods · A/B testing · Experimental design
Neural architecture design · Optimization methods · A/B testing · Experimental design
Certifications
AI Professional Program
Stanford University Online Education
XCS224R: Deep Reinforcement Learning — In progress · XCS236: Deep Generative Models — Enrolled
Applications of ML in Medicine
Stanford University Online
XMLPH110: Completed May 2026 · XMLPH120: In progress
Deep Learning Specialization
deeplearning.ai / Coursera · May 2018
Neural Networks • CNNs • Sequence Models • Structuring ML Projects
Education
Ph.D. Electrical–Electronics Engineering
Çukurova University · 2012–2015
M.Sc. Computer Engineering
Çukurova University · 2010–2012
B.S. Computer Engineering
Çukurova University · 2006–2010