Waabi is a Toronto-based developer of autonomous trucks built on a Physical AI approach. Its stack pairs PyTorch, CUDA and TensorRT with a graphics toolchain (Vulkan, OpenGL, GLSL, RenderDoc) plus ISO 26262, pointing to heavy investment in GPU-optimized ML and in-house simulation under functional-safety rules. Hiring skews senior and engineering-heavy, with a meaningful ops layer tied to fleet uptime and the push toward fully driverless operation.
Waabi, founded in 2021 and headquartered in Toronto, develops AI systems for autonomous trucking, positioning the work as a first application of Physical AI. The company is privately held and employs between 51 and 200 people. Its engineering work spans perception, machine learning, simulation and vehicle hardware, using languages including Python, C++, Go and Rust on AWS and GCP infrastructure. Alongside engineering and research, it runs fleet operations teams and hires across Canada and the United States.
Waabi uses Python, C++, Go and Rust with PyTorch, CUDA, TensorRT and TensorFlow for ML, Bazel and Docker for builds, AWS and GCP for cloud, and Vulkan, OpenGL and Three.js for graphics and simulation.
Waabi is headquartered in Toronto, Canada, and hires in both Canada and the United States.
Waabi is building its Waabi World simulator, generative scenario modeling for safety-critical testing, HIL bench software, data annotation tooling and hardware end-of-line testers, while working toward fully driverless trucks.
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Waabi's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
