Software Engineer, Labelling, Data & Automation

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai As a Software Engineer on our Labelling and Data Automation team, you will build pipelines, tools, and workflows to accelerate the development of our AI-first self-driving technology. The Labelling & Data Automation team plays a critical role in Waabi’s training pipeline. We are one of the first steps in the process of training machine learning models and are responsible for building practical, scalable tools and automation for extracting interesting and relevant data, creating high-quality ground truth labels, and providing this data to our expert machine learning scientists and engineers. You will.. - Design and implement tools, pipelines, and metrics to accelerate the development of our AI-first autonomy system and generative AI simulator. - Own the process, criteria, and tooling for efficiently finding interesting and relevant data across the petabytes of real world data that Waabi has collected - Build high reliability systems for extracting and labelling the interesting data with various vendors and integrate it back into our system - Work with both internal and third party stakeholders to define taxonomy, validation rules and success criteria for our labelling projects - Design and manage the end-to-end deployment of data solutions to deliver high quality labelled data for various ML teams to use in experiments and model improvement - Deploy open-set / embedding models to our production environment - e