Software Engineer, AI/ML Infrastructure

Role overview

Build and improve the shared infrastructure that enables product and science teams to develop, deploy, and operate AI and machine-learning applications at scale. The work spans backend services, execution systems, model integrations, and the tools used throughout the model lifecycle, from training and data workflows to evaluation and production serving.

Responsibilities

- Develop core platform capabilities that let teams build, run, and scale AI-powered applications. - Help design, implement, and deploy infrastructure for model training and serving, feature and data workflows, CI/CD, orchestration, deployment, and evaluation. - Work across backend services and execution infrastructure, connecting platform systems with AI models and related tools. - Collaborate with experienced engineers to assess emerging infrastructure frameworks and tools for product use. - Deliver projects with attention to measurable outcomes and business impact. - Investigate complex technical problems and keep current with developments in AI infrastructure.

Requirements

- At least 2 years of professional software engineering experience. - Strong grounding in data structures, algorithms, and software design. - Proficiency in a major programming language and willingness to work across languages; Go and Python are used in the existing stack. - Experience with relational or NoSQL databases, such as PostgreSQL or DynamoDB. - Ability to use AI coding tools in everyday work and critically review, validate, and refine their output. - Comfort learning unfamiliar technologies and moving work forward amid ambiguity and changing priorities.

Benefits and work setup

The source lists an expected salary range of $123,300–$159,500 for candidates based in Ontario or British Columbia. Actual offers may vary based on role level and the candidate’s qualifications and skills.