We're hiring a Planning & Controls Engineer in our Autonomy Software team. In this role, you'll own and develop flight control, motion planning, and mission planning algorithms for robust, fault-tolerant drone delivery. This is a hands-on role: you will design controllers, implement them in C++ on embedded platforms, test them in flight, and iterate.
You're excited about this opportunity because you will...- Play an integral role on a small and focused team
- Develop and tune low-level flight control algorithms for overactuated multirotor and hybrid aircraft on embedded platforms
- Own the dynamics simulation and aerodynamics modeling of the aircraft
- Bring up and tune flight controllers on new drone platforms
- Develop, tune, and test fault-tolerant control (loss of one or more motors, safe landing, emergency behaviors)
- Build a trajectory motion planner for smooth flight and obstacle avoidance within the operating envelope
- Help develop the high-level mission route planner with fallback locations
We're excited about you because...- You have deep controls fundamentals: linear and nonlinear systems, stability analysis, controller synthesis and tuning, frequency domain analysis, optimization, and linear algebra
- You have excellent knowledge of C++ and embedded systems
- You bring dynamics modeling and simulation experience with aerodynamics knowledge
- You have experience developing and tuning flight controllers, interfacing with state estimation
- You have excellent knowledge of motion planning algorithms (trajectory optimization and nonlinear optimization, A*/D*/RRT variants)
- You have experience with sensorless brushless DC motor control
- You've built or owned a robot control stack end-to-end, from design through implementation to hardware testing
- MS/PhD degree in EE, ME, CS, Robotics, or related technical field
- Nice to have experience includes:
- Familiarity with PX4 internals (mixer, rate controller, position controller)
- Experience with hybrid VTOL transition control
- Experience with tethered or suspended payload dynamics
- Contributions to open-source flight stacks or robotics frameworks
- Published papers in controls, motion planning, or aerial robotics
- Experience developing a Model Predictive Controller (MPC), including formulation, solver, and deployment
CompensationThe successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee's work location. Ranges are market-dependent and may be modified in the future.
In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
DoorDash cares about you and your overall well-being. That's why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
To learn more about our benefits, visit our careers page here.
See below for paid time off details:
- For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
- For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).
The national base pay range for this position within the United States, including Illinois and Colorado.
$198,600-$292,000 USD
