Jobs at Waabi

The role involves building standardized training frameworks, profiling model performance, collaborating with teams, and improving related tooling.

The role involves designing and implementing MLOps pipelines, optimizing machine learning processes, and ensuring model performance and compliance in a collaborative environment.

The Applied Data Scientist will analyze performance data of Waabi's autonomy systems, develop automated dashboards, and collaborate across teams to drive insights for performance improvements.

Lead development of web tools for autonomous driving, mentor engineers, and collaborate on technical architecture, focusing on responsive applications and cloud infrastructure.

The role involves designing frameworks for autonomy evaluation, implementing performance measurement methodologies, and developing analytical models for self-driving technologies. The applied scientist will collaborate with cross-functional teams, prototype analyses, and ensure rigorous evaluation standards are met.

Lead the financial close process, manage consolidations, ensure accurate US GAAP reporting, automate accounting tasks with AI, and support audits.

The Systems Engineer will develop and implement safety frameworks for autonomous technology, analyze performance metrics, and ensure safety readiness through simulation and testing.

Own verification of autonomous platform software: create verification plans, build and maintain test infrastructure and CI, run automated tests, analyze large datasets, improve high-fidelity simulation, and validate AV software releases across localization, planning, and control modules.

Lead the strategy and execution of the autonomy stack for Waabi Driver, ensuring alignment across teams, managing product lifecycles, and making data-driven decisions to commercialize autonomous features.

As a Research Engineer in Sensor Simulation, you will develop multi-sensor rendering systems for self-driving technologies, collaborate with scientists and engineers, and work on innovative solutions using machine learning and neural rendering techniques.

The Senior Manager will cultivate relationships across government levels, track legislation, build support programs, and represent Waabi in industry associations, with a focus on Canadian policy and public affairs.

The Distillation Lead will define and implement strategies for model distillation and compression, collaborating with various teams to deliver efficient models for real-time systems and simulations.

Design and develop Waabi's observability stack, optimize performance, build automation tooling, and support application requirements while leading projects and mentoring teams.

The role involves developing low-level embedded software for vehicle control, integrating sensors, collaborating with various teams, and ensuring safety standards are met while mentoring junior developers.

Develop and maintain production-quality software for self-driving technology. Collaborate with teams, lead discussions, and mentor engineers.

As a Senior or Staff Software Engineer on the Localization team, you will design algorithms for state estimation systems, optimizing multi-sensor data fusion for real-time vehicle localization in autonomous driving.

As a Senior Software Engineer on the Mapping team, you will architect and develop robust, scalable systems for autonomous vehicle mapping, collaborating with multidisciplinary experts and handling complex data processing.

Lead cross-functional platform integration programs, mapping dependencies across hardware, embedded software, autonomy, safety, and operations. Define integrated plans, track VnV and test campaigns, surface risks with data-backed mitigation options, own executive reporting, and build scalable processes, tooling, and dependency maps to deliver milestones on time at fleet scale.

As a Research Engineer, you will integrate ML models into planning stacks, develop testing interfaces, and collaborate with teams to enhance autonomous truck capabilities.

As a Research Engineer, you will develop algorithms for world models focusing on generative and predictive modeling within complex environments, optimizing model deployment, and collaborating with research teams.