Welcome to my website, I am Mostafa M. Amin
— Generative AI, Deep Learning, and Algorithms.
I combine PhD-level research depth with hands-on product experience to ship AI systems that are testable, reliable, and cost-aware—spanning architecture, offline/online evaluation, and deployment.
How can I help you?
Here are my professional offerings, engagements, and ways we can work together.
Process Automation with Generative AI
Turn business processes into reliable, measurable GenAI automation — avoiding "AI for AI’s sake."
- Hybrid Architecture & Design: Decompose workflows to strictly separate GenAI from deterministic logic, delivering containerized technical blueprints (Docker/K8s) for seamless handover.
- Quantitative Evaluation: Replace subjective "vibes" with golden datasets, synthetic test generation, and automated regression pipelines to prove reliability.
- Production Readiness: Implement safety guardrails, drift monitoring, and robust failure patterns to ensure the system evolves without breaking.
Typical Deliverables: End-to-end architecture diagrams, deployment specifications, evaluation suites, and risk/fallback strategies.
End-to-End Model Development & Deployment
End-to-end development of production-grade ML/DL systems for text, audio, and affective computing — from experiment design and training to deployment and safe continuous improvement.
- Rigorous experiment design: modeling choices, metrics/robustness criteria, baselines & ablations, and strong hyperparameter optimization strategies
- High-quality data pipelines: preprocessing, dataset QA, audio/text quality measurement, and targeted augmentation (where appropriate)
- Reproducible model development: classical baselines → LSTM/GRU → transformer encoder(-decoder) stacks, plus tracking, checkpointing, and resume-safe training
- Production deployment & lifecycle: Docker-first serving, versioned APIs, regression gates, monitoring (drift/quality/cost), safe retraining, and rollback paths
Experience
Selected highlights from my CV.
Experiences & Education
- Senior Researcher in Generative AI at Dynatrace.
- Senior Research Data Scientist at SYNCPILOT, 7 years of experience.
- Software engineering internships at Google (Paris) and Facebook (NYC).
- Ph.D., University of Augsburg (2019-2024), with guest contributions at TUM (2024).
- 10+ peer-reviewed publications across affective computing, NLP, and LLM evaluation.
- Best Student Paper Award at IEEE CBMS 2021.
- Competitive Programming ICPC World Finalist and multiple regional champion teams.
Contributions
- Developed LLM-based agentic developer tools.
- Developed advanced RAG pipelines with hierarchical chunking of code and fine-tuning embeddings.
- Built streaming multimodal AI systems for real-time personality prediction from Audio; end-to-end from training to deployment.
- Contributed to the open-source deep learning library Keras.
- Mentored engineers and researchers in ML and NLP domains.
- Experience presenting to technical and non-technical audiences.
- Active contributor to AI and programming communities: judging and coaching.
- Adaptable and collaborative team player in diverse environments.
- Strong foundation in algorithms, data structures, and competitive programming.