Safety Methodologies Internship/Co-op 2027
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Sep 10, 2026. Waabi scores A on the Alion truth index.
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.