MLOps Engineer

Loopio; Toronto; Remote; CAD 80,000 - 110,000; Full time

Job summary

Join a leading company as an MLOps Engineer, where you will scale and productionize machine learning systems. Collaborate with a dynamic team to build robust ML pipelines and ensure reliable model deployment. Embrace a remote-first culture with flexible work options and a commitment to professional growth.

Benefits

Comprehensive health and wellness benefits

Monthly phone and internet subsidy

Home office setup budget

Professional mastery allowance for learning

Qualifications

• 2+ years of experience in ML operations or related infrastructure roles.
• Strong Python development skills with solid software engineering practices.

Responsibilities

• Build and maintain robust ML pipelines for training and deployment.
• Package and deploy models into production environments using Docker and Kubernetes.
• Implement systems to monitor model health and detect drift.

Skills

MLOps Experience

Cloud & Infrastructure Skills

Software Engineering Foundation

Model Deployment & Monitoring Tools

Team Collaboration

Growth Mindset

Tools

Docker

Kubernetes

AWS

Airflow

MLflow

SageMaker

TensorFlow Serving

TorchServe

Job description

Join to apply for the MLOps Engineer role at Loopio

Get AI-powered advice on this job and more exclusive features.

Take your career to new heights with Loopio!

We’re looking for a skilled and motivated MLOps Engineer to help scale and productionize the machine learning systems that power Loopio’s intelligent product features. In this role, you’ll work closely with ML Engineers, Data Scientists, and Backend Engineers to build the pipelines, infrastructure, and tooling needed to deliver high-impact ML models to our users reliably, efficiently, and at scale.

You’ll be a critical part of enabling our AI/ML roadmap, from intelligent search and content suggestions to document automation and agent copilots, by ensuring models can be deployed, monitored, and continuously improved in production environments.

This is a great opportunity to grow your expertise in applied MLOps, contribute to high-leverage systems, and be part of a fast-moving, collaborative team working at the intersection of ML, engineering, and product.

What You’ll Be Doing

1. Pipeline & Workflow Development: Build and maintain robust ML pipelines for training, evaluation, and deployment. Automate routine workflows and support reproducible, auditable experimentation.
2. Model Deployment & Inference: Package and deploy models into production environments using tools like Docker, Kubernetes, and SageMaker. Build REST/gRPC services to serve models in real-time or batch.
3. Monitoring & Reliability: Help implement systems to monitor model health in production, detect drift, and log predictions. Contribute to alerting and dashboarding that helps the team maintain trust in deployed models.
4. CI/CD for ML: Work within our CI/CD systems to support model validation, promotion, and rollback. Help build safe, automated workflows for taking models from development to deployment.
5. Collaboration & Support: Partner with ML Engineers and Data Scientists to bring ML systems into production. Contribute to shared libraries, improve developer experience, and help debug operational issues. Partner with Infra and DevOps teams to understand their tooling deeply in order to help implement ML systems and related cloud architecture.

What You’ll Bring To The Team

1. MLOps Experience: 2+ years of experience working in ML operations, ML engineering, or related infrastructure roles. Familiarity with deploying ML models and automating ML pipelines.
2. Cloud & Infrastructure Skills: Comfort working with AWS (or similar cloud environments), Docker, and Kubernetes. Experience with workflow orchestration tools like Airflow, Dagster, or Kubeflow is a plus.
3. Software Engineering Foundation: Strong Python development skills, with a solid understanding of software engineering practices (testing, logging, version control, code review).
4. Model Deployment & Monitoring Tools: Experience with tools such as MLflow, SageMaker, TensorFlow Serving, or TorchServe. Bonus: hands-on experience implementing model monitoring or drift detection systems.
5. Team Collaboration: Comfortable working cross-functionally with technical and non-technical stakeholders. Curious, communicative, and open to feedback. Willing to learn from others and share what you know.
6. Growth Mindset: You’re excited about learning the ins and outs of ML systems in production. You bring energy, ownership, and a desire to build things that are both elegant and effective.

Where You’ll Work

• Loopio is a remote-first workplace because we recognize the advantages of working flexibly. We are HQ’d in Canada, with established hub regions around the world where we hire from.
• Our employees (or Loopers, as we call ourselves!) live and work in Canada (British Columbia and Ontario), London, and India (specifically in Gujarat, Maharashtra, and Bengaluru).
• The majority of our team is based in ON and BC, which means these employees live and work remotely within a 300km radius of Toronto (Ontario) and Vancouver (BC).
• We offer flexible co-working locations available to Loopers in ON and BC. Those based in ON have the option of working out of our convenient co-working space located in Downtown Toronto, near Union Station. BC Loopers can work centrally in Vancouver. It’s flexible to what suits you best!
• You’ll collaborate with your teams virtually across the UK, India, and North America (just a Zoom call and Slack message away!), with core sync hours and focus time for heads-down work during the workday.
• We encourage asynchronous collaboration to work effectively as a global #OneTeam!

Why You’ll Love Working at Loopio

• Your manager supports your development through ongoing feedback and regular 1-on-1s, using tools like Lattice for performance conversations.
• You will have opportunities to elevate your craft and explore your creativity, supported by a professional mastery allowance for learning. We encourage experimentation and innovative thinking to drive impact.
• We offer comprehensive health and wellness benefits starting from day one.
• We’ll set you up to work remotely with a MacBook, a monthly phone and internet subsidy, and a home office setup budget.
• You’ll be part of a supportive culture with opportunities for connection in a remote environment.
• Participate in townhalls, AMA sessions, and celebrations to mark milestones as #oneteam!
• Our Employee Resource Groups provide opportunities to learn and connect throughout the year.
• Be part of an award-winning workplace where you can make a significant impact.

Additional Notes

We encourage candidates who may not meet every requirement to still apply, as we value diverse experiences and backgrounds. Share more about yourself in the application prompts, especially if transitioning careers or self-taught. We leverage AI responsibly in our recruitment process, supporting efficiency and reducing bias, but all final decisions are made by our team. Loopio is committed to diversity and inclusion, welcoming applicants from all backgrounds. Contact us at [e-mail] for accommodations at any stage.