Ariz Ahmad
Software Engineer
Software Engineer based in Atlanta, GA, USA. AI / Machine Learning Engineer with strong software engineering foundations and experience owning production ML and GenAI systems end-to-end. Designed and deployed scalable data and model pipelines across feature generation, training, evaluation, and cloud deployment. Experienced in LLM-powered applications (RAG,agents) with a focus on latency, reliability, performance, and maintainability.
Get in TouchWork Experience
Microsoft
Data Software Engineer
Feb 2022 — Present- Led onboarding of 15+ enterprise teams data to a large-scale analytics platform supporting downstream ML and AI workloads, migrating 200+ TB of data while implementing enterprise-grade security controls (RBAC, encryption, Azure Key Vault).
- Led adoption of AI-assisted development workflows across a 30+ engineer organization by evaluating LLM tools, defining usage guidelines, and training developers, resulting in a 25–35% reduction in development time and improved code consistency.
- Built and maintained CI/CD pipelines for data and ML-adjacent services using Azure DevOps, enabling automated testing, deployment, and monitoring; reduced release cycles by 60% with 99.9% success across 50+ production releases.
- Designed and optimized Spark-based data pipelines used for analytical and ML use cases, reducing query latency by 40% and enabling faster feature generation for downstream models.
University of Florida
Research Volunteer
Aug 2021 — Feb 2022- Developed deep learning models for protein structure prediction using PyTorch, CNNs, and RNNs on large-scale PDB and UniProt datasets; built automated preprocessing pipelines for 500K+ protein sequences, reducing manual data preparation time by 80%.
- Improved fold classification accuracy by 20% over sequence-based baselines using ensemble methods and hyperparameter tuning, while reducing training time by 40% and maintaining 95%+ cross-validation accuracy for secondary structure prediction.
Samsung Research Institute
Software Developer - Android
Jul 2016 — Aug 2019- Developed and optimized Android applications for Samsung Galaxy devices used by 50+ million users, maintaining a 99.5% crash-free rate across production releases.
Featured Projects
About Me
"I believe the best AI systems are built with intentionality and craftsmanship. As an ML engineer, I'm committed to more than just accuracy metrics—I care deeply about system reliability, performance optimization, and code quality. Whether designing data pipelines, developing RAG systems, or deploying LLM applications, I bring a software engineer's rigor to every project, ensuring solutions are maintainable, scalable, and production-ready."
