At Prime Video I engineered large-scale personalization and retrieval systems powering millions of transactions per second across global storefronts. I conceived a patent-pending recommendation strategy, aligned product, science, and engineering teams, and built the DynamoDB-based online serving architecture paired with Spark-trained contextual bandits—driving the largest subscription-start increase in PV history (~8M annually).

I delivered integrity-critical recommendation systems (Top 10 charts, full-catalog embedding scoring), and scaled nearest-neighbor retrieval using FAISS. I also identified and resolved distributed caching flaws that saved millions in infra costs, implemented cross-region failover with stronger freshness guarantees, and integrated backend support for early LLM-based semantic grouping.

Since joining March Networks, I accelerated the company’s analytics initiatives and contributed to the development of core technologies and architectures that underpin their video analytics platform. I trained, tuned, and optimized neural networks for real-time inference on edge devices such as NVIDIA Jetson and Ambarella CVflow, demonstrating their impact on critical business use cases. I also led end-to-end design and development of computer vision systems for physical security applications, spanning model development, embedded deployment, and cloud-based search workflows.

I led the design and development of systems that continue to deliver value to clients in the advertising and data analytics space. My work included building robust data-ingestion pipelines, designing distributed computing workflows to generate high-quality business insights, and implementing CI/CD and Kubernetes-based deployment processes. I also expanded my leadership capabilities by hiring and managing small engineering teams to unify data platforms, unlock value from large impression and location datasets, and deliver reliable, user-facing technology.

For my second internship at Pythian, I returned with the need to learn an entirely new technology stack to contribute to their early startup, now a spin-off company known as "Tehama". I was quickly introduced to Nodejs, cloud technologies, and full-stack application development. After a few months, I became a key contributor to many of the business critical components of the platform.