About this role
Staff Systems Engineer - Safety Methodologies is a remote position based in the US and Canada focused on leading safety framework methods for driverless autonomy readiness. This role suits an experienced engineer with a background in automotive or robotics looking to shape safety validation for autonomous trucking solutions.
Role Overview
Waabi seeks a Staff Systems Engineer - Safety Methodologies to lead safety framework methods that support driverless autonomy readiness decisions. The position involves establishing safety evaluation pipelines, utilizing realistic simulation and real-world data, and creating structured safety artifacts for autonomous vehicle operations.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Waabi operates as a technology start-up focused on physical AI and autonomous transportation, powering commercial trucks and robotaxis. Founded by Raquel Urtasun, the organization maintains offices in Toronto, San Francisco, Dallas, and Pittsburgh, and partners with leaders across AI, automotive, logistics, and deep tech.
How to Apply
To apply for this position, please visit the official Waabi careers page.
Skills and tech stack
Questions candidates ask
What is the salary range for the Staff Systems Engineer role?
The US yearly salary range for this position is $200,000 to $256,000 USD, supplemented by discretionary equity awards, performance bonuses, and competitive benefits.
Where is the position located?
This role is available as a remote position across the US and Canada.
What level of experience is required?
Candidates must have 7 or more years of industry experience in automotive, robotics, or a closely related field.
What educational background is needed?
An undergraduate degree in an engineering discipline is required, with a Master's or PhD preferred.
What technical skills are necessary?
The role requires strong scripting and data analysis skills in Python and SQL, a solid background in statistics, and experience with simulation and real-world testing.