Teams at Rebar

Build backend systems that translate computer vision and machine learning outputs into interactive product experiences. Responsibilities include designing perception-to-product data contracts, shipping AI-generated geometry to a canvas, balancing accuracy with user experience, closing human correction loops, and bridging AI/ML and product engineering teams. The role requires Python and TypeScript, familiarity with PyTorch and model postprocessing, data contract versioning, and experience deploying computer vision or ML outputs in user-facing products.

Build and own full-stack product features for a collaborative browser-based canvas editor used on large construction drawings. Responsibilities include improving rendering performance, interaction latency, memory usage, client-side state, collaborative document architecture, testing, APIs, database models, and production reliability. The role requires deep React and TypeScript expertise, browser performance experience, backend fundamentals, and ownership of complex production systems. This is an onsite role in New York City.

Lead and scale Rebar’s end-to-end client implementation and onboarding function. Build repeatable workflows, playbooks, training, metrics, and operational systems while supporting customized enterprise and SMB implementations. Manage and develop Implementation Managers, partner cross-functionally with Sales, Client Success, Product, and Engineering, resolve complex onboarding issues, improve time to value and adoption, and influence product improvements. The role includes onsite client travel approximately once per month.