Robotics Controls Engineer

An innovative medical device company is looking to bring on controls engineer for a 3 month project (that could extend) in Culver City, CA. This growing company develops miniature remotely actuated robots that navigate the central nervous system. The miniature robots are controlled via external electromagnetic fields, thus allowing safe and simple motion in the human body. This person will work on the R&D team and lead the development of control algorithms that will enable our novel magnetic propulsion system to accurately control their devices. We are looking for someone to focus on image processing and develop their proof of concept for their upcoming program.

Qualifications:

1. 8 to 10 years of hands-on experience working on controls of robotics or other complex electromechanical systems requiring physics-based modeling, and image processing/machine learning.
2. Extensive experience in hands-on programming in Python and C/C++
3. Demonstrable experience applying a data driven and scientific approach to R&D engineering problems and statistical analysis of real-world data, and large data sets.
4. MS in Mechanical Engineering, Electrical Engineering, Computer Science, Physics, or equivalent.
5. Experimental experience, using sensors, DAQ, MCUs, etc.
6. Experience in bringing products to market in a regulated industry such as Medical, Autonomous vehicles/drones, Defense, Aerospace, or Gaming/Entertainment.

Responsibilities of Position:

1. Develop control algorithms that accurately and robustly propel this device to its desired anatomical location using both classical and modern control methodologies.
2. Build effective state estimation systems and signal processing algorithms to sense and localize the device
3. Optimize control algorithm with respect to multiple constraints and different cost functions.
4. Lead statistical data analysis efforts, in particular timeseries, and real-world multidimensional data robustness
5. Design and conduct physical experiments and iteratively improve control algorithms based on experimental findings and theoretical considerations.
6. Lead risk analysis and risk mitigation efforts.
7. Develop timelines and deliver on agreed-upon milestones.
8. Collaborate with a multidisciplinary team including electrical/mechanical/software engineers, materials scientists, and clinical professionals.

$60 – $70 an hour depending on experience and education level but pay is flexible