Build and scale critical infrastructure for low-latency model deployment and distributed inference pipelines. Optimize platform bottlenecks and implement robust CI/CD and observability loops to support internal ML research scientists.
Design and optimize high-performance model serving infrastructure and real-time performance engines using Rust. Replace high-overhead bottlenecks with memory-safe, low-latency systems to support petabyte-scale data processing.
Design, build, and deploy production ranking and recommendation models directly within customer environments to optimize business conversion. Manage the end-to-end ML lifecycle, including data pipeline architecture, model monitoring, and the development of repeatable deployment patterns.
Build and scale robust, concurrent core platform components and architect composable systems for high transactional throughput. Define the long-term technical vision and collaborate with ML research scientists to prototype and launch new capabilities.
Drive full-cycle enterprise sales cycles for Fortune 500 retailers and travel companies, managing complex eight-figure deals from initial conversation to expansion. Collaborate with internal technical and executive teams to build rigorous business cases and lead successful product evaluations.
Own the end-to-end marketing function, including strategy, budget, and team leadership to drive demand for a category-defining AI platform. Lead positioning, messaging, and ABM strategies targeting Fortune 500 enterprises in retail, marketplaces, and travel.
Act as a technical advisor and partner to customers to ensure the successful deployment and stabilization of AI-powered workflows. Translate customer needs into product feedback to guide the evolution of the company's ranking models and API systems.
