About the role

We are looking for bright engineers interested in designing elegant solutions to difficult problems in the autonomy space. Your contributions will focus on building out capabilities of an autonomous vehicle stack, including necessary enablement work on the infrastructure- and vehicle-side. At Applied Intuition, we encourage engineers to take ownership over technical and product decisions, interact closely with users & customers to collect feedback, and contribute to a thoughtful, dynamic team culture.

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 Intuition, you will:

• Design and implement motion planning and controls modules that can be deployed on various vehicle platforms, enabling them for highly accurate autonomous navigation in tight scenarios.

• Characterize the dynamics of our customers’ vehicles to create tailored controls solutions and to reduce the gap between simulation and real-world dynamics.

• Evaluate and utilize academic research to create optimal-control-based solutions using techniques like nonlinear MPC and MPPI control.

We're looking for someone who has:

• Passion about tackling challenging motion planning or motion control problems.

• 3+ years of experience building production software using modern software practices.

• Hands-on experience testing controls solutions on real, production-grade vehicles.

• Fluency in control theory, numerical optimization, numerical analysis, and physics.

• Enthusiasm for coming up with practical solutions to cutting-edge challenges in a fast-paced environment.

• Experience writing high-performance C++ code.

Nice to have:

• MSc or PhD in mechanical engineering or computer science with coursework or research experience in motion planning or controls.

• Experience writing software that is compliant with guidelines for safety-critical C++ code, such as MISRA and AUTOSAR.

• Experience using quadratic programming solvers or nonlinear optimization tools.

• Experience applying machine learning techniques to vehicle dynamics modeling.

• Experience working both with large industrial /commercial vehicles, as well as passenger cars.