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Engineer - Reinforcement Learning

    • Waterloo, Ontario
  • etthy

Job description

Huawei Canada has an immediate a 12-month contract opening for an Engineer.

About the team:
The Intelligent Complex Systems Team, currently a part of the Waterloo Research Centre, examines recent advancements in artificial intelligence (AI) and robotics to determine its potential for broader applications. This innovative team researches AI challenges such as matching human capabilities and ensuring the safety of collaborative AI systems.

About the job:

  • Design and develop Reinforcement Learning solutions for self-adaptive systems to go beyond what current AI-based application can do

  • Proactively engage in research activities and identify new opportunities for research; present research findings and progress updates to team members and stakeholders, as well as work with cross-functional teams to integrate them into practical applications

  • Work cross-functionally to set the broader strategy and roadmap

  • Mentor and guide junior team members to support their growth and development.

  • Develop collaboration with external partners and research institutions to foster innovation and expand the reach of our research

Job requirements

About the ideal candidate:

  • MS or PhD in in Computer Science, Software Engineering, Robotics or Artificial Intelligence with a strong focus on Reinforcement Learning and AI system design

  • 3+ years of experience in research or industry roles related to Reinforcement Learning

  • Knowledge on applications of Reinforcement Learning at Runtime leveraging operational data and feedback from the environment

  • Familiar with state-of-the-art Reinforcement Learning algorithms

  • Proficiency in Python prototyping

  • Industry experience with exploration of various Reinforcing Learning technologies for different domains (e.g. automotive, robotics)

  • Research or design experience developing self-adaptive systems or Online/Continual Reinforcement Learning-based systems

  • Proven track record of publications in relevant AI, SE, or RE venues

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