Senior MLOps Engineer

T-Net British Columbia; Toronto; Hybrid; CAD 100,000 - 130,000; Full time

Job summary

A technology company is looking for a Senior MLOps Engineer to join its Engineering team. This role, available to candidates across Canada, focuses on building scalable infrastructure for GenAI solutions. Candidates should have strong Python or Ruby skills and expertise in cloud infrastructure. The position involves remote work with a minimum of two office days per week for local candidates. This is an exciting opportunity to drive impactful AI projects.

Qualifications

• Strong Python or Ruby development skills, experience building production-grade applications.
• Expertise in cloud infrastructure including Kubernetes and infrastructure-as-code.
• Experience with automating model training and CI/CD pipelines.

Responsibilities

• Build and deploy LLM-based solutions for clients.
• Collaborate with cross-functional teams for new ML features.
• Troubleshoot production issues and contribute to architectural decisions.

Skills

Python or Ruby development

Cloud infrastructure expertise

CI/CD automation experience

Machine learning knowledge

Leadership skills

Problem-solving abilities

Tools

AWS

GCP

Azure

Kubernetes

Terraform

Helm

Job description

Posted July 8, 2025
Toronto / Remote - Canada

We are currently seeking a Senior MLOps Engineer to join our Engineering team. This role is available to candidates across Canada. If you are local to one of our hubs (Burnaby, Calgary, or Toronto) you will be expected to be in office minimum two days per week for our Anchor Days.

What your team does:

Our MLOps team builds and operates the scalable infrastructure and robust platforms that power GenAI solutions across the company. We blend deep AI and ML expertise with strong software engineering and cloud infrastructure skills to enable the entire lifecycle of machine learning and generative AI - spanning experimentation, deployment, monitoring, and continuous improvement. By applying best practices in CI/CD, observability, cost optimization, and model governance, and leveraging state-of-the-art tools and frameworks, we ensure our AI systems are reliable, performant, and aligned with business goals. We partner closely with data scientists, engineers, and product teams to accelerate the delivery of impactful AI capabilities.

What a day in the life might look like:

• Build and deploy LLM-based solutions that help Clio's clients save time and improve operational efficiency.
• Collaborate cross-functionally with engineering, product management, operations, and data science to identify and develop new ML-driven features.
• Work agilely alongside MLOps, MLE, and full stack developers on diverse projects spanning multiple engineering teams across three countries.
• Evaluate and integrate new ML tools and frameworks to accelerate experimentation and optimize operations.
• Troubleshoot and resolve production issues such as data drift and model latency using observability tools and logs.
• Participate in design reviews and contribute to architectural decisions shaping Clio's AI platforms.
• Engage in code reviews within your team and across the company, providing and receiving constructive feedback to maintain high standards.
• Continuously learn, challenge yourself, and grow as a machine learning expert while mentoring and collaborating with teammates.

What you may have:

• Strong Python or Ruby development skills, with experience building production-grade applications, services, or ML tooling.
• Expertise in cloud infrastructure (AWS, GCP, or Azure), including Kubernetes, and infrastructure-as-code (Terraform, Helm, or similar).
• Experience with CI/CD and automating model training, testing, and deployment pipelines.
• Solid understanding of machine learning and GenAI concepts, workflows, and lifecycle management.
• Demonstrated leadership skills, with the ability to mentor and guide team members effectively.
• Demonstrated ability to fully own the design and delivery of robust, scalable solutions from concept through implementation.
• You excel at breaking down complex, challenging problems into manageable parts and iterating toward effective solutions.
• You are naturally curious and love to dig deep into problems, constantly asking,