Research-oriented Systems Engineer with 2+ years building scalable ML infrastructure and simulation environments for agentic AI systems. Specializing in designing training environments inspired by world models and JEPA (Joint Embedding Predictive Architectures), with strong interest in neurosymbolic AI approaches for robust reasoning.

Currently expanding expertise in reinforcement learning environment design and LLM fine-tuning through hands-on implementation. Proven track record implementing ML pipelines and building rigorous evaluations measuring genuine model capabilities beyond standard benchmarks.

Demonstrated high agency by leading NASA-nominated AI project from concept to global recognition. Deep technical experience across distributed systems, containerization (Docker, Kubernetes), and production ML operations, balancing research exploration with engineering rigor.