ExaCare
Machine Learning Engineer
Remote Toronto & Vancouver, Hybrid in New York · Remote · Full-time · Posted Feb 27, 2026
- Experience
- 3+ years in one or more of the listed fields: machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments.
About the job
Build and operate the infrastructure, workflows, and tooling that bring machine learning models into reliable, scalable production systems.
What you'll do
- Build and maintain end-to-end ML lifecycle infrastructure, including data and training pipelines and deployment workflows.
- Partner with researchers and ML practitioners to productionize models and improve data processing and annotation workflows.
- Monitor and improve ML system reliability, scalability, observability, efficiency, and cost; automate bottlenecks.
What they ask for
- 3+ years of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments.
- Experience supporting ML systems end to end, from model handoff through deployment and monitoring.
- Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML.
- Strong software engineering fundamentals and experience building production systems; experience monitoring, debugging, and improving production ML or data systems.
AI focus
Operationalize and scale ML systems, including productionizing models and supporting training, inference, deployment, and performance monitoring.
Model-written summary · the original posting is authoritative