Remote job · IT and software
Machine Learning Operations Developer, Inference, AI/ML Platform
In one line: Machine Learning Operations Developer, Inference, AI/ML Platform is a remote role in Canada at a global 3D design and engineering software company.
- Remote (Canada)
- A global 3D design and engineering software company
- Posted 9 Oct 2026
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https://keywordise.com/mcpApply to Keywordise job he6f4wpkmtAbout the role
Join an AI/ML platform team to keep machine learning models running smoothly and the platform efficient. The role supports generative AI and ML solutions behind a product suite.
At a glance
- PayNot stated in the posting
- Remote scopeRemote, Canada
- Posted9 Oct 2026
- Last checked19 Oct 2026
What you will do
- Implement and refine MLOps practices to keep the AI/ML platform operationally strong
- Build and maintain automated pipelines that move models from development into production
- Design and maintain scalable infrastructure for training, inference and data processing
- Create monitoring and logging systems that track model performance and system health
- Apply version control and model governance, including compliance and data privacy
- Automate processes, resolve operational issues and support incident response
What they look for
- BS or MS in computer science or a related field
- Two or more years of hands-on DevOps and MLOps work deploying models in production
- Infrastructure as Code experience with tools such as Terraform or Ansible
- Containerization skills with Docker and Kubernetes for scaling ML workloads
- CI/CD pipeline setup and upkeep for machine learning projects
- Scripting in Python, Bash or similar for operational automation
Nice to have
- Familiarity with databases and data storage
Questions about this job
Is this job fully remote, and from where?
Yes, it is listed as remote, aimed at candidates in Canada.
What does this job pay?
No pay range is stated in the posting.
What experience is needed?
The posting asks for: BS or MS in computer science or a related field; two or more years of hands-on DevOps and MLOps work deploying models in production; infrastructure as Code experience with tools such as Terraform or Ansible.
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