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Senior Robotics Software Engineer

2 months ago

Toronto, Ontario, Canada Ocado Logistics Full time

Senior Robotics Software Engineer

Ocado Logistics is a leading robotics and artificial intelligence (AI) company that develops robots to solve real-world problems. Our mission is to enhance the lives of human workers with the power of AI robotics. Our cutting-edge technology is the foundation of a number of proprietary platforms, including CORE with AutoGrasp, developed to operate robots autonomously in dynamic environments. Our team of scientists, engineers, and business operators have set a new standard for reinforcement learning for robots. We are a global company with a presence in San Francisco and Toronto, and we are part of the UK-based Ocado Group plc.

Every day will bring new and exciting challenges on the job while you:

  • Develop, evaluate, and optimize algorithms related to the production of advanced robotic products.
  • Implement new control algorithms and experiment/characterize physical hardware.
  • Perform simulation runs to validate mathematical models, new parameters, and algorithms.
  • Investigate new technologies, identify bottlenecks, improve processes, create roadmaps, and further robotics software development and robotics research at Ocado Logistics.
  • Mentor, grow, and motivate junior team members, interns, and peers.

What you bring:

  • Experience programming with Python, C, and/or C++.
  • Experience modeling robotic manipulators.
  • Experience in robotics, machine learning, and optimization.
  • Understanding of modeling and control algorithms for robotic systems.
  • Understanding of learning-based algorithms and their application to robotic systems.
  • Experience working with robotic sensors such as cameras and force sensors.
  • Ability to work in a team, transfer knowledge, and mentor.

Bonus qualifications:

  • Master's or Doctorate degree in engineering with a focus in robotics or similar experience.
  • Experience simulation through Matlab.
  • Experience with adaptive, optimal, and learning-based control for robotic manipulation.
  • Familiarity with robotic applications that involve contact with the environment and manipulation.
  • Experience working with different robotic grippers.
  • Experience using physics-based simulation to develop robot control policies.
  • Experience with real-time control.