I’m a results-driven ML/MLOps engineer with 7+ years of experience building, deploying, and scaling ML/AI systems across multi-cloud environments (AWS, Azure, GCP). I specialize in MLOps pipelines, CI/CD, observability, infrastructure-as-code, container orchestration, and LLMOps. I excel at turning AI research into production-grade solutions that drive measurable business outcomes.
I thrive on delivering secure, reliable, and scalable AI systems by collaborating with cross-functional teams, implementing robust monitoring, and automating end-to-end model lifecycles. My focus is on reducing downtime, optimizing latency, and accelerating ML lifecycle automation to enable rapid, safe adoption of AI in production.
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