- Location
- Toronto, ON · San Francisco, CA · Pittsburgh, PA · Remote US & Canada
- Workplace
- Hybrid, Remote
- Type
- Full-time
- Department
- Software
- Seniority
- Senior
- Experience
- 6+ years
- Education
- PhD
- Source
- Lever
Description
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
At Waabi, we are building the next generation of autonomous driving technology, leveraging a revolutionary approach to Physical AI. Central to our success is the ability to monitor and report on the performance of our software, platform, and fleet with rigor and reliability.
We are looking for a highly experienced Applied Data Scientist to play a leading role in shaping the methodologies underlying our evaluation ecosystem. This is a senior technical role that sits at the intersection of Evaluation, Systems & Safety, and the Autonomy teams. You will help co-design and build the rigorous frameworks that validate the Waabi Driver across Waabi World (Simulation), Track, and Public Road testing.
You will...
- Design scalable production frameworks for autonomy evaluation. You will apply statistically rigorous methodologies to challenges such as sampling evaluation sets to ensure comprehensive Operational Design Domain (ODD) coverage.
- Design and implement methodologies to systematically measure and monitor the performance, fidelity, and reliability of the evaluation infrastructure itself, ensuring our testing ecosystem remains a highly trusted source of truth.
- Directly prototype complex deep-dive analyses, write production-quality evaluation code, and build the sophisticated tools and dashboards that synthesize our progress for technical and executive leadership.
- Act as a key partner to Safety and Autonomy teams, ensuring that our automated reporting faithfully captures the technical intent and requirements of our system.
- Develop advanced analytical models to help correlate closed-loop simulation performance with real-world driving outcomes, quantifying the fidelity and predictive power of our evaluation metrics.
- Serve as a subject matter expert and collaborative partner, elevating the analytical bar of the team through code reviews, methodological guidance, and helping to define best practices for end-to-end data science workflows.
Qualifications:
- Minimum of 6+ years of professional experience in an applied data science, advanced analytics, or machine learning role, with a track record of driving end-to-end projects.
- MS/PhD or equivalent experience in a highly quantitative field such as Statistics, Mathematics, Computer Science, Physics, or Robotics.- Strong command of Python/SQL for data analysis and prototyping
- Expertise in statistical methods, including hypothesis testing, A/B testing on complex systems, sampling methodologies, and statistical modeling.
- Experience working with internal cross-functional partners/stakeholders
- Open-minded and collaborative team player with willingness to help others- Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
Bonus/nice to have:
- Experience in the Autonomous Vehicle or Robotics industry
- Familiarity with Systems Verification and Validation
- Experience with large scale databases and analytics
- Experience with workflow automation/orchestration frameworks
Skills
PythonSQLMachine LearningData SciencePrototyping
