Senior AI Engineer
New
We sent a six-digit code to . Enter it below — or use the link in the same email.
Or click the link in the same email — either works.
Enter the email address on your account and we'll send you a link to set a new password.
Remembered it? Sign In
Looking for an AI engineer job in Toronto? Choose from 24 open roles at 12 employers. Explore real salary data and skills breakdown across remote, hybrid and on-site roles.
Free. No credit card needed.
In the week to 27 September, 30 AI engineer roles were open in Toronto at 13 employers. 5 new roles were posted during the week. Of the roles that say how they work, 27% are remote or hybrid.
Among the AI engineer roles listed on the board, the balance skews heavily toward experienced practitioners. Lead-level positions account for the largest share, with senior roles not far behind; intern positions make up a much smaller portion. Most postings have appeared within the past month, with a healthy share arriving in just the past week, suggesting employers are actively recruiting rather than running aged listings. Agents, Python, evaluation frameworks and APIs are each mentioned in most descriptions, pointing to a consistent set of expectations across employers. A notable share of the roles on the board are concentrated among a relatively small number of hirers, which reflects a market shaped by a few well-resourced organisations hiring at scale.
Figures are measured every Monday.
AI engineers build, integrate and maintain systems that put machine-learning models to practical use. The work typically spans designing pipelines for large language models, building retrieval-augmented generation systems, writing and managing APIs, and keeping deployments running reliably through CI/CD practices. In a city like Toronto, with national AI research infrastructure through the Vector Institute, a strong foundation-model company in Cohere, and major financial institutions headquartered nearby, AI engineers may find themselves working on anything from enterprise document processing to fraud detection to health-technology products. The MaRS Discovery District and the DMZ also generate a stream of start-ups where an AI engineer may take on broader responsibilities across the full stack.
Python is mentioned in a large majority of descriptions alongside agent frameworks and LLM-related work, so fluency in all three is clearly expected. Evaluation — assessing model behaviour in production — appears almost as often, which is worth treating as a first-class skill rather than an afterthought. RAG, AWS and Azure each appear in roughly half of descriptions, and prompt engineering, Docker, CI/CD and SQL are each mentioned in about a third, rounding out a practical engineering toolkit.
The employers' own advertised ranges, for individual roles at different levels — not an average and not a market rate.
On-site work is strongly dominant among the roles listed here, accounting for nearly three quarters of those stating a preference. Hybrid arrangements make up most of the remainder, leaving fully remote positions as a very small minority. Candidates expecting flexible location arrangements will find them, but should expect most employers to want regular in-office presence.
Jobs checked 14 minutes ago.
Search by role, company, or anything a posting mentions.
