About
I turn messy ML experiments into systems that actually run at scale. I build machine learning systems that don’t fall apart in production.
My work focuses on the intersection of AI research, infrastructure engineering, and system architecture.
I have led the design of end-to-end ML platforms, enabling teams to move from fragmented experimentation to structured, reproducible, and production-ready workflows.
Platform Engineering
Architecting ML platforms from scratch, orchestration, scheduling, observability, and lifecycle management across distributed systems.
AI & Research
Reinforcement learning, generative models, evolutionary algorithms, and multi-agent systems, with a focus on bridging research and production environments.
Infrastructure
Kubernetes, Nomad, cloud systems, and scalable pipelines designed for high-performance ML workloads and GPU-aware execution.
My Story
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