AI/ML Engineering for trustworthy intelligent systems
I design, build, and evaluate intelligent systems that ship—from ML pipelines and LLM applications to the cloud-native infrastructure that keeps them fast, observable, and reliable.
Ph.D. researcher in Computer Science at the University of Southern Mississippi, focused on trustworthy AI, ML systems, and cloud-native deployment.
Ph.D. research focus
Trustworthy intelligent systems. Built to ship.
Multimodal & vision–language models
Systems that reason across vision, language, and other modalities—built for real-world inputs, not just benchmark scores.
Agentic AI & reinforcement learning
Autonomous agents that plan, act, and learn from feedback—sequential decision-making designed for production constraints.
Adversarial robustness & safe deployment
Defending intelligent systems under attack, benchmarking failure modes, and shipping guardrails teams can measure and trust.
From models to systems that hold up in production.
I'm Olanrewaju (Ola) Muili—an AI/ML engineer and Ph.D. student in Computer Science at the University of Southern Mississippi in Hattiesburg, MS. My Ph.D. research centers on trustworthy intelligent systems—multimodal perception, agentic decision-making, and adversarial robustness—backed by cloud infrastructure and operational practices that survive incident pressure. The full arc is on About.
I ship in public and in production. Tracevox is an open-source LLM observability platform—tracing, cost analytics, and incident workflows for AI workloads in production. I care about architectures teams can actually run: measurable quality, clear APIs, and infrastructure that keeps intelligent services healthy under stress.
Before software, I worked as an Exploration Geologist—building 3D models and data-heavy workflows for resource projects. That path taught me to reason under uncertainty, document rigorously, and deliver across disciplines. I bring the same discipline to designing ML systems, evaluating model behavior, and building cloud platforms that teams can trust.