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AI / Machine LearningRemote

ML Platform Engineer at Themis Solutions

Themis Solutions - Company

Canada, ๐Ÿ‡จ๐Ÿ‡ฆ CanadaFull-time - Senior (4-7 years)0 applicantsCloses Jul 15, 2026

Salary

CAD 152,000 - 152,000 / year

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Job description

Job details

  • Location: Canada
  • Work mode: Remote
  • Employment type: Full-time (Not an internship)
  • Salary: CAD 152,000 per year

Role overview

Themis Solutions is seeking a skilled ML Platform Engineer to join the Engineering team. In this role, you will build and maintain the infrastructure necessary to deploy and scale legal AI technology, ensuring that legal professionals can work more efficiently and securely. This is a full-time position open to candidates across Canada.

Job details

This position is based in Canada and offers a Remote work mode, with optional access to hubs in Toronto, Calgary, or Burnaby. This is a full-time professional role and is not an internship. The offered salary for this position is 152,000 CAD.

Responsibilities

  • Design and implement scalable infrastructure for deploying machine learning models.
  • Collaborate with data scientists to optimize the ML lifecycle from training to production.
  • Maintain and improve the reliability and performance of the AI platform.
  • Develop automated pipelines for continuous integration and continuous deployment of ML models.
  • Monitor system health and performance to ensure high availability of AI services.

Requirements

  • Proven experience as an ML Platform Engineer or DevOps Engineer with a focus on AI.
  • Strong proficiency in Python and experience with ML frameworks like PyTorch or TensorFlow.
  • Experience managing containerized workloads using Kubernetes and Docker.
  • Knowledge of cloud service providers such as AWS, Azure, or GCP.
  • Ability to build robust data pipelines and manage large-scale datasets.

Benefits

  • Competitive annual salary of 152,000 CAD
  • Flexible remote work options across Canada
  • Opportunity to work with industry-leading legal AI technology
  • Professional growth in a high-impact engineering environment

Keywords

MLOpsMachine LearningPythonKubernetesCloud InfrastructureAI PlatformCI/CDModel Deployment