Artificial Intelligence (AI)/Machine Learning (ML) Engineer/Scientist

at  Aviya Aerospace Systems

Aviya Aerospace Systems is a leader in engineering services and solutions for mission critical Aerospace and Defense applications. Aviya provides expertise in program management, systems, software, mechanical, and hardware engineering to many of the top-tier Aerospace and Defense Contractors. Aviya may have an upcoming opportunity for an Artificial Intelligence (AI)/Machine Learning (ML) Engineer/Scientist to join our engineering group in Mississauga, Ontario or Longueuil, Quebec. While we are not hiring for this position, at the moment, we are actively collecting resumes from qualified candidates to prepare for potential opportunities.

QUALIFICATIONS FOR POSITION

• Master’s or PhD degree in science or engineering.
• Minimum 5 years of experience working on machine learning projects.
• Must be a Canadian Citizen.
• Proficiency in deep learning models for embedded systems.
• Familiarity with various neural networks, computer vision, and artificial intelligence.
• Strong communication skills, both written and verbal.
• Ability to work collaboratively in a team environment.
• Strong problem-solving skills with the ability to think analytically and logically.
• Please note that this position may be in-office 5 days/week or hybrid, this is TBD.
  For further information please visit us at www.aviyatech.com
  Aviya Aerospace Systems is an equal opportunity employer and is committed to fostering a diverse and inclusive work environment. Upon request, Aviya will accommodate candidates with disabilities throughout the hiring process up to the point of undue hardship.
  Thank you for your interest in Aviya Aerospace Systems. We are diligently reviewing every application, however only those applicants selected to move onto the next step will be contacted

• Design, optimize, and maintain electro-optic/infrared data collection systems.
• Manage and curate data throughout the machine learning development lifecycle, while creating and validating custom solutions.
• Implement machine learning products on hardware accelerators and integrate them into embedded systems.
• Develop strategies to address optimization challenges.