Waabi, founded by AI pioneer and visionary Raquel Urtasun, is an AI company building the next generation of self-driving technology. With a world class team and an innovative approach that unleashes the power of AI to “drive” safely in the real world, Waabi is bringing the promise of self-driving closer to commercialization than ever before. Waabi is backed by best-in-class investors across the technology, logistics and the Canadian innovation ecosystem.
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
At the heart of our mission is an unwavering commitment to safety. We are seeking a passionate and experienced safety or systems engineer to spearhead the development and implementation of critical safety framework methods that underpin our driverless autonomy readiness decisions. This is a unique opportunity to shape how Waabi quantitatively ensures and validates the safety of our autonomous trucking solution, working with our highly realistic simulator, real-world data, and cutting-edge generative AI techniques. You will play a pivotal role in creating the evidence for safe operation and leading efforts in a rapidly evolving and groundbreaking field.
You will…
- Scale and manage safety framework methods by defining requirements for automated assessment workflows and partnering with the autonomy and algorithms teams to implement and debug the evaluation infrastructure.
- Develop and monitor quantitative metrics to evaluate system performance against established safety targets.
- Optimize test coverage within Waabi’s high-fidelity simulator to validate driving behaviors across safety-critical scenarios.
- Define and iterate on human performance benchmarks to support robust comparative safety assessments.
- Identify safety gaps and ensure traceability between requirements, validation artifacts, and safety case claims.
- Maintain structured documentation of safety artifacts and readiness decisions to ensure rigorous transparency and traceability.
- Mentor peers to foster technical excellence and drive constructive cross-functional collaboration.
Qualifications:
- Undergrad required; Masters or PhD within an engineering discipline preferred.
- 5+ years of automotive, robotics or related industry experience.
- Experience contributing to the development of a safety case for autonomous vehicles.
- Experience with using simulation and real-world testing to make readiness decisions.
- Knowledge of relevant safety methods and standards such as STPA, SOTIF (ISO 21448), ISO/SAE PAS 22736, and UL 4600.
- Strong fundamentals in mathematics, engineering and physics.
- Excellent scripting and data analysis skills with tools such as Python and SQL.
- Ability to communicate complex concepts or data in a simple-yet-accurate manner.
- Collaborative team player who works effectively across functional boundaries.
- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
Bonus/nice to have:
- Experience in launching a driverless product.
- Experience in data science and machine learning
- Experience implementing software systems components.
- Advanced skills in data mining, mathematics, and statistical analysis.
