We’re looking for an experienced Infrastructure Engineer who will bring focus and subject-matter expertise around AWS, on-premise deployment methods, and container frameworks. This is a unique opportunity to grow in the world of machine learning infrastructure and work with a team of passionate individuals committed to the mission of bringing ML to enterprise.
At Borealis AI, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at borealisai.com.
Your responsibilities include:
Building highly scalable, resilient cloud and on-premise systems for hosting machine learning systems using state-of-the-art technologies;
Designing, building, and optimizing comprehensive automation systems that operate the business’s web, mobile and data infrastructure platforms;
Deploying and managing cloud services on AWS, Azure, etc.;
Leveraging modern tools to define, build, and manage virtual infrastructure in the cloud (primarily on AWS);
Configuring automated service deployments with tools such as Ansible, Puppet, Chef or similar;
Collaborating with engineers, and machine learning researchers to consolidate ML frameworks and to automate code analysis, build, and integration.
You're our ideal candidate if you have:
Strong and relevant experience designing and implementing distributed systems;
Hands-on experience building and deploying virtualized environments in major cloud environments, such as AWS and Azure;
Solid understanding of the UNIX operating system;
Experience automating infrastructure, testing, and deploying cloud applications with tools such as Ansible, Jenkins, etc.;
Experience with monitoring and alerting solutions, like ELK stack and CloudWatch;
Experience on Jenkins, including setting up Jenkins pipelines to enable CI/CD.
It would be great if you also have:
Production software development experience;
Development, deployment, or maintenance of machine learning applications;
Implementing monitoring solutions to identify and implement system bottlenecks and production issues;
Familiarity with machine learning frameworks such as PyTorch, TensorFlow, Keras, Theano, and/or similar.
What's in it for you?
Become part of a team that thinks progessively and works collaboratively. We care about seeing each other reach full potential;
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
Leaders who support your development through coaching and managing opportunities;
Ability to make a difference and lasting impact from a local-to-global scale
Borealis AI, a RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.