Skip to content

Artificial Intelligence – Machine Learning Engineer

  • Full Time
  • Toronto

Iris Software Inc.



Our Client which is a large Publishing Firm is urgently looking for AI/ML Engg.

AI/ML Engg.



No. of Roles – 2

Candidate to work as per EST Timings only.

Skills – AWS SageMaker, Developed and Implementing AI Models, Strong Python/PySpark

  • Lead design, development, implementation, and maintenance of AI platform & AI powered tools / applications.
  • Stay up to date with the latest advancements in AI technologies, exploring opportunities to integrate new AI capabilities into existing or new applications.
  • Work with a team of individual contributors through leadership and delegation, along with your own hands-on contributions, to build our web applications, including building entirely new applications, making major product updates, and maintaining our existing portfolio. Our products at McGraw Hill are used by millions of people every day. Some have an SLA of 99.95% uptime; stability and quality solutions are key!
  • Work with product, engineering, SRE, and other leadership to understand how your solutions will be planned, developed, implemented, and supported.
  • Implement best practices for application security and ensure compliance with relevant data privacy and protection regulations.
  • Contribute to CI/CD processes to allow for smoother releases and increasing team confidence.
  • Use your interpersonal skills and ability to collaborate effectively with product sponsors and senior leadership in engineering and the greater business.
  • Understand the business requirements of products, tasks, and stores, and if you identify possible gaps, ambiguities, missing scenarios, opportunities, etc., raise them with the team and with leadership so we can all improve them.
  • Work with a distributed team to solve problems quickly and collaboratively.
  • Consider the full lifecycle of solutions when building them from initial conception to launch then maintenance all the way to sunsetting.


About You:

  • You have experience developing AI powered solutions at an enterprise level.
  • You have led a team of individual contributor engineers, having come from an engineering background yourself. You have empathy for engineers and balance that with realities of the business.
  • You interface well with other business units and leadership, being able to describe situations and technical approaches to foster an environment of trust and confidence.
  • You have deep expertise developing both front-ends and back-ends of modern web applications and have a general understanding what is involved in front-end development as well.
  • You build front-ends with the needs of our users in mind, partnering with our UX team members to build the best experiences for our teachers, students, and other personas.
  • You consider the needs of accessible designs in all steps of the engineering process for those with visual, auditory, sensory, cognitive, and other considerations.
  • You design APIs that are meant to be consumed by others, so ease of use, simplistic design, and other attributes that benefit interoperability are key.
  • You believe in understanding why work is being done and empathizing with the users, not just implementing code and moving onto the next task.
  • You have demonstrated software delivery experience with a distributed product & engineering team.
  • You can work in a fast-paced software release environment, where you continuously deliver production-grade (near-zero downtime, fault-tolerant, etc.) software daily for a system with millions of users around the world.
  • You have contributed to the full software development life cycle, including writing application code, unit/integration/automation tests, documentation, and performance engineering and security.

We have a very diverse stack that can vary across teams and projects. Some of the technologies we use include:


Back-end: Python, Go, Node.js

Front-end: TypeScript, Angular, React and Playwright


AI services such as Azure AI Search, Azure OpenAI service, Amazon Bedrock or similar technologies.

Amazon Web Services (AWS): ECS, RDS, Lambda, and many other services


CI/CD and Infrastructure: Docker, Terraform, Github, CircleCI, Sonarqube, NewRelic and Datadog

Collaboration: JIRA, Confluence, Zoom, Slack, and Office 365


Databases: Relational databases such as MySQL and PostgreSQL; NoSQL databases such as DynamoDB