Full-Time

AI Engineer

Updated on 8/23/2026

Armilla AI

Armilla AI

No salary listed

Toronto, ON, Canada

Hybrid

Hybrid work environment based in Toronto's Liberty Village.

Category
Software Engineering (1)
Required Skills
Scikit-learn
Microsoft Azure
Python
TensorFlow
PyTorch
Machine Learning
Version Control
AWS
Web Development
DevOps
Google Cloud Platform
Requirements
  • Strong engineering skills and a proven track record in software development.
  • A solid understanding of the AI model lifecycle, especially AI model evaluations.
  • In-depth knowledge of AI pipelines and experience building, managing, and optimizing them for product development and evaluation.
  • Demonstrable experience applying software engineering best practices to machine learning projects.
  • Proficiency in creating end-to-end software stacks, including front-end and back-end development.
  • Hands-on experience deploying and managing applications on major cloud service providers such as AWS, Google Cloud Platform, or Microsoft Azure.
  • Strong programming skills in Python.
  • Experience with relevant artificial intelligence and machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn.
  • Problem-solving abilities and a commitment to producing high-quality, maintainable code.
  • Strong communication and collaboration skills for working effectively in a cross-functional team.
Responsibilities
  • Collaborate with senior artificial intelligence and machine learning scientists and product managers to design, build, and maintain an adversarial artificial intelligence evaluation platform.
  • Architect and implement programmatic platforms for evaluating artificial intelligence models, including assessing performance, robustness, and potential risks.
  • Implement and optimize artificial intelligence pipelines for data flow, model training, inference, and evaluation processes.
  • Apply software engineering best practices to machine learning projects, including version control, automated testing, code reviews, and continuous integration and continuous deployment.
  • Develop and integrate user interface and user experience components for internal tools and evaluation platforms.
  • Deploy and manage artificial intelligence applications and evaluation infrastructures on cloud service providers such as AWS, Google Cloud Platform, and Microsoft Azure.
  • Collaborate with data scientists, actuaries, and product managers to translate complex requirements into robust technical solutions.
  • Troubleshoot, debug, and optimize existing artificial intelligence systems to improve performance and stability.

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