Autonomy and Perception Engineer | US or CA Citizen

Work with a small, fast-moving and motivated team delivering next-generation legged robots for industrial, military and public safety applications.  Self-motivated, solid work ethic and ability to execute under demanding timelines. Strong growth opportunity, and ability to help set the R&D direction as the company expands. 

Ghost is venture financed with enormous potential to change the landscape of autonomous legged robotics with commercialization opportunities in industrial, defense and consumer segments. The company recently won the Innovation Award at AUVSI Defense Conference, and was a finalist for the NVIDIA AI Inception Awards.

Citizenship Requirements

United States or Canadian citizenship necessary to work with certain DoD technology 

Minimum Experience Level

3 years in robotics or related field. Preferably with enterprise and/or DoD applications


Master's or PhD in robotics or related field from a recognized institution


Philadelphia, PA


  • Implement state-of-the-art fully autonomous behaviors and logic for legged based robots

  • Develop AI capable of performing tasks day in and day out without any human intervention

  • Integrate deep learning and other forms of advanced machine intelligence to improve robustness of AI

  • Implement state-of-the-art fully autonomous behaviors and logic for legged robots

  • Develop low level safeguard autonomy to prevent the robot from taking harmful actions 

  • Field test, debug and maintain autonomous software stack

  • Optimize existing autonomous framework for use on embedded devices

  • Develop high level API to interface with the robot

  • Communicate and work seamlessly with other peers to ensure all responsibility are carried out

Qualifications and Experience 

  • Ability to read and write production level code in C/C++ while following best practices using git source control

  • Self sufficient in integrating 3rd party libraries based on very limited/no documentation and reverse engineering

  • Ability to code algorithms from academic papers

  • Competent with advanced data structures, and very comfortable composing multiple transforms

  • Thorough understanding of computer vision approaches as described in the book Multiple View Geometry

  • Modifying and training deep learning models using TensorFlow and/or Caffe and interfacing in C++ environment

  • Working with computer vision systems on robots and with sensor fusion using graph based optimization

  • Has implemented SLAM on a robot in some form or fashion 

  • Experience with Vision Aided Inertial navigation and 3D reactive path planning 

Apply​ with qualifications and cover letter

Apply​ with qualifications and cover letter

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