Principal DevOps Engineer (AI/ML Infrastructure)
JobgetherThis position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Principal DevOps Engineer (AI/ML Infrastructure) based in CanadaÂ
We are looking for an experienced Principal DevOps Engineer to design, build, and manage the infrastructure powering advanced AI and machine learning capabilities within a modern SaaS platform. In this senior technical role, you will drive the development of scalable, secure, and reliable AI/ML environments, supporting the entire lifecycle from experimentation and data ingestion to model deployment and production monitoring. You will work closely with AI researchers, software engineers, and cross-functional R&D teams to bridge the gap between research and production-ready solutions. Your expertise will help optimize infrastructure performance, automate complex workflows, and accelerate AI innovation. You will also serve as a technical leader and mentor, promoting engineering best practices and driving continuous improvement. This is an opportunity to contribute to impactful scientific software solutions within an international, innovation-driven environment.
Accountabilities
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Architect, design, and lead the implementation of scalable, secure, resilient, and high-performance infrastructure to support demanding AI and machine learning workloads.
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Build, maintain, and optimize specialized CI/CD pipelines for AI/ML applications, covering the complete lifecycle from data ingestion and model development to deployment, serving, and monitoring.
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Design and manage cloud-based AI/ML infrastructure, leveraging containerization, orchestration, and platform engineering technologies to ensure scalability and operational efficiency.
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Drive automation across infrastructure provisioning, model deployment, testing, and operational workflows to improve reliability, consistency, and development speed.
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Collaborate closely with AI researchers, data scientists, and software engineers to streamline experimentation processes and translate machine learning models into reliable production applications.
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Ensure the security, availability, reliability, and performance of AI/ML systems through effective infrastructure management, monitoring, and continuous optimization.
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Act as a technical subject matter expert, mentoring junior engineers and promoting best practices in AI/ML platform development, source control, automation, and deployment.
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Identify emerging technologies, tools, and industry trends, evaluating innovative solutions that can strengthen infrastructure capabilities and accelerate AI/ML development.
Requirements:
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At least 5 years of professional experience in DevOps, machine learning infrastructure, or platform engineering, including several years in a senior technical or leadership capacity.
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At least 5 years of advanced experience with one or more major cloud platforms, such as AWS, Microsoft Azure, or Google Cloud Platform (GCP), including their AI/ML and containerization services.
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Minimum 5 years of hands-on experience with machine learning orchestration and platform technologies such as Kubeflow, MLflow, or Amazon SageMaker.
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Approximately 5–8+ years of strong expertise in Docker and Kubernetes, particularly for deploying, managing, and scaling AI/ML workloads.
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Approximately 5–8+ years of programming experience with languages such as Python, Go, or Bash, with a strong focus on scripting and infrastructure automation.
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Experience with infrastructure-as-code and configuration management tools such as Terraform or Ansible.
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Demonstrated ability to design and implement reliable automated CI/CD pipelines using tools such as GitHub Actions, GitLab CI/CD, or Jenkins.
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Strong understanding of DevOps principles, cloud infrastructure, container orchestration, automation, scalability, and security best practices.
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Excellent communication and collaboration skills, with the ability to work effectively alongside AI researchers, software developers, infrastructure specialists, and business stakeholders.
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Strong technical problem-solving skills, initiative, and the ability to drive complex infrastructure projects independently.
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A valid LinkedIn profile and relevant professional work links must be included with your application.
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Must be based in Canada and available to work Eastern Standard Time (EST) business hours.
Benefits:
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Competitive annual base salary: CAD $130,000–$165,000, depending on experience, qualifications, work location, and internal compensation considerations.
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Fully remote opportunity: Work remotely from anywhere within Canada.
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Full-time position: Long-term opportunity in a newly created role.
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Technical leadership: Take ownership of strategic AI/ML infrastructure initiatives and influence platform engineering practices.
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Professional development: Work with modern cloud technologies, machine learning platforms, container orchestration, and advanced automation tools.
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Collaborative environment: Partner with experienced AI researchers, software engineers, and R&D professionals.
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Innovation and impact: Contribute to the development of AI-powered scientific software solutions supporting research, discovery, and innovation.
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Additional employee benefits may be available depending on the position and employment package offered.