Applied Intuition
Software Engineer - Low Speed Motion Planning & Control
About this role
Applied Intuition seeks a Software Engineer to design and implement motion planning and control systems for autonomous vehicles. You'll work on production-grade solutions that enable accurate autonomous navigation across various vehicle platforms, combining control theory with real-world vehicle testing.
What you'll do
- Design and implement motion planning and controls modules for autonomous vehicle platforms
- Characterize vehicle dynamics and create tailored control solutions to improve simulation-to-reality accuracy
- Develop optimal-control solutions using techniques like nonlinear MPC and MPPI control
- Test and validate controls solutions on production-grade vehicles
- Evaluate and integrate academic research into practical autonomy applications
- Collaborate with customers to collect feedback and inform technical decisions
What they're looking for
- Motion planning and control theory
- Numerical optimization and analysis
- High-performance C++ development
- Vehicle dynamics characterization
- Production software development practices
- Physics and systems modeling
- Real-world vehicle testing experience
- Nonlinear MPC and MPPI control techniques
Benefits
- Equity compensation (options and/or RSUs)
- Comprehensive health, dental, vision, life and disability insurance
- 401k retirement benefits with employer match
- Learning and wellness stipends
- Paid time off
- Flexible work arrangements with primarily in-office expectations
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Applied Intuition
Applied Intuition builds autonomous vehicle and defense systems software, including motion planning algorithms, simulation infrastructure, and autonomy integration platforms for aerial and ground platforms. The company is hiring for security engineers, robotics/autonomy software engineers, hardware-in-the-loop specialists, and IT operations professionals to support its growing physical AI operations.
- Website
- appliedintuition.com
Likely interview questions
- Walk us through a production vehicle control system you've built or deployed—what were the key challenges in bridging the simulation-to-reality gap?
- Describe your experience with nonlinear MPC or MPPI control. How have you applied these techniques to solve a real motion planning problem?