Design and implement safety-critical planning systems for autonomous vehicles in a dynamic team at Applied Intuition.
Posted by employer 4 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Skills & Technologies
Requirements
Not disclosed in this posting: compensation, visa sponsorship.
Joblaze summary
In the role of Senior Software Engineer - Planning at Applied Intuition, the individual will focus on designing and implementing deterministic motion planning systems for autonomous vehicles, ensuring safe behavior under various conditions. Key skills include a strong background in robotic motion planning algorithms, proficiency in C++, and experience with safety-critical systems. This position is ideal for seasoned engineers with over five years of relevant experience who thrive in a fast-paced, collaborative environment. The company emphasizes excellence and innovation in the rapidly evolving field of autonomy.
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About the role
As a Motion Planning Engineer, you will design and ship deterministic, safety-critical planning systems that ensure autonomous vehicles behave safely when autonomy degrades or operates under uncertainty. This role emphasizes classical motion planning, predictable behavior, and large-scale evaluation, rather than deep learning–driven planning.
In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the nascent autonomy industry. We move fast and we focus on excellence, for our products and for our business. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied is the place for you!
At Applied, you will:
Design and implement classical or ML motion planners for fallback and minimal-risk maneuvers.
Build planners that operate reliably under degraded perception, partial observability, and system faults.
Define and execute safe, deterministic vehicle motions such as controlled slow-downs, pull-overs, and safe stops.
Use large-scale simulation and real-world data to evaluate planner behavior and guide parameter tuning.
Develop metrics, analysis tools, and dashboards to understand planner performance at scale.
Collaborate closely with behavior prediction, perception, controls, safety, and remote assistance teams.
Contribute to a reusable fallback platform used across trucking and other autonomy programs.
We’re looking for someone who:
5+ years of experience in motion planning for autonomous vehicles or robotics.
Strong foundation in robotic motion planning algorithms and trajectory generation (optimization-, search-, or rule-based).
Experience building deterministic, safety-critical planning systems.
A data-driven mindset for large-scale evaluation, debugging, and tuning of planning behavior.
Proficiency in C++ and experience working in real-time systems.
Strong systems thinking and cross-functional collaboration skills.
Nice to have
Experience designing minimal-risk maneuvers (MRM) or emergency handling behaviors.
Familiarity with AV safety concepts, ODD constraints, or safety-case-driven development.
Experience using ML techniques for parameter tuning, calibration, or offline optimization.
Experience working with degraded sensors, uncertainty, or human-in-the-loop systems.
Background in simulation frameworks or large-scale log analysis.
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