Safety Methodologies Internship/Co-op 2027

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 the heart of our mission is an unwavering commitment to safety. We are seeking a curious and analytical Safety Methodologies Intern to support the development and implementation of the frameworks that underpin our driverless readiness decisions. This is a unique opportunity to gain hands-on experience in the autonomous vehicle industry, and you will be helping us quantitatively validate the safety of our autonomous trucking solution using our highly realistic simulator and real-world data. We are looking for a driven, inquisitive self-starter who will use their diverse background to dive headfirst into our data and tooling to generate actionable insights for the Safety team.

Application Instructions:

- To be considered for an internship/co-op, please add your most up to date academic transcripts alongside your resume for further review.

- The Summer Internship is expected to start May/June 2027 and continue on a full-time basis (40 hours/week) to August/September 2027.

You will…

- Develop Python scripts and tools to calculate quantitative metrics and visualize complex data for collision assessment.

- Support optimization of data pipelines and automated assessment workflows used for safety validation.

- Explore large crash databases and apply multivariate modeling techniques to predict collision related metrics. Gain an in-depth understanding of the ins and outs of publicly available safety resources.

- Conduct A/B testing on collision models using metrics that you develop within the context of our broader safety framework.

- Collaborate with the safety team to integrate the models you develop into safety evaluation pipelines.

Qualifications:

- Currently pursuing a Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Mathematics, Statistics, or a related field.

- Experience identifying and handling missing values, anomalies, and outliers in large-scale, real-world datasets.

- Solid foundation in regression, classification, and hypothesis testing, with the ability to surface patterns in large-scale tabular data.

- AI-native — uses AI tooling to rapidly experiment, prototype, and harden code, and can rigorously validate the results.

- Strong Python scripting skills, including hands-on experience with data manipulation libraries (e.g., Pandas, NumPy).

- Able to communicate complex technical concepts clearly and accurately.

- Collaborative team player who works effectively across functional boundaries.

- Genuinely excited about self-driving technology and drawn to solving hard, unsolved problems.

Bonus/nice to have:

- Previous internship or academic experience in robotics, automotive, or data science.

- Experience with SQL or other data mining tools.

- Experience creating data visualizations or dashboards.