Alpesh VIRANI

Architected the end-to-end strategy, deployment, and commercialization of enterprise Machine Learning products on cloud platforms to power Twin's successful, AI-driven diabetes reversal product. Modernized and migrated existing ML data cleansing and inference pipelines into a highly scalable infrastructure. Successfully integrated LLMs, AI, and IoT data streams into the core data pipeline to unlock predictive analytics and enhance product performance.

Designed, developed, and deployed scalable data pipelines processing daily performance metrics across 4G, 5G, Wi-Fi, and legacy networks for 80,000+ smartphones. Engineered the core infrastructure for Nielsen Mobile Performance, capturing massive datasets used by Sprint, T-Mobile, AT&T, and Verizon. Managed high-throughput ingestion of mobile analytics, tracking application and IP usage, voice, battery metrics, roaming data, and YouTube/Facebook performance.

Worked on calculate TV show rating for real time streaming data from steupbox.

Worked with different clients Apple, Wells Fargo, Hitachi, and Eaton. Worked on scalable AWS Cloud environments and the Hadoop ecosystem to build data warehousing. Worked on Java development and full-stack web development, creating secure data-driven applications and optimizing automated data reporting layers. Delivers high-performance, regulatory-compliant data solutions that seamlessly bridge the gap between legacy infrastructure and modern cloud architectures.

worked on Parallel algorithm, MPI, Java, MPI Cluster, Grid comp, Numerical Algorithm, QR algorithm, Intel thread profiler and scientific computing algorithm