MLOps Engineer

Loopio; Ontario; Remote; CAD 80,000 - 120,000; Full time

Job summary

Loopio is seeking a skilled MLOps Engineer to enhance their machine learning systems. In this role, you will collaborate with ML Engineers and Data Scientists to develop robust ML pipelines, deploy models, and ensure reliability in production environments. This position offers a unique opportunity to grow your expertise in MLOps while working within a dynamic and supportive team.

Benefits

Health and wellness benefits

Remote work setup with MacBook

Flexible co-working locations

Professional mastery allowance for learning

Qualifications

• 2+ years of experience in ML operations or related infrastructure roles.
• Strong Python development skills and understanding of software engineering practices.
• Experience with tools like MLflow, SageMaker, TensorFlow Serving, or TorchServe.

Responsibilities

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

SageMaker

Job description

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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

• Pipeline & Workflow Development: Build and maintain robust ML pipelines for training, evaluation, and deployment. Automate routine workflows and support reproducible, auditable experimentation.
• 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.
• 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.
• 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.
• 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

• 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.
• 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.
• Software Engineering Foundation: Strong Python development skills, with a solid understanding of software engineering practices (testing, logging, version control, code review).
• 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.
• 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.
• 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 (within Ontario) and Vancouver (Within 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 the heart of Downtown Toronto and a 12-minute walk from Union Station. BC Loopers have the option to work centrally in Vancouver. It is whatever works best for you!
• You’ll collaborate with your teams virtually across the UK, India, and North America (we’re just a Zoom call and Slack message away!) with core sync hours and focus time for headsdown work during the workday
• We encourage asynchronous collaboration to effectively work as a global #OneTeam!
  
  

Why You’ll ️ Working at Loopio

• Your manager supports your development by providing ongoing feedback and regular 1-on-1s, we leverage Lattice for our 1:1s and performance conversations
• You will have the opportunity to elevate ???? your craft and the opportunity to explore your creativity, with a dedicated professional mastery allowance for more learning support! We encourage experimentation and innovative thinking to drive business impact.
• We offer a wide range of health and wellness benefits to support your physical and mental well-being, starting day with Loopio.
• We’ll set you up to work remotely with a MacBook laptop , a monthly phone and internet subsidy, and a work-from-home budget to help get your home office all set up.
• You’ll be joining a supportive culture that has thoughtfully built out opportunities for connections in a remote first environment.
• Participate in townhalls, AMA (Ask-Me-Anything), and quarterly celebrations to celebrate the big wins and milestones as #oneteam!
• Our four active Employee Resource Groups offer opportunities for employees to learn and connect year-round.
• You’ll be a part of an award-winning workplace with an opportunity to make a big impact on the business.
  
  

Questioning your qualifications? Read this ️ Hi there, we recognize that all too often, potential candidates don’t apply for a position simply because they don’t hit every single criteria included in the job description—particularly members of underrepresented groups.

Whether or not your experience checks off all the boxes on a job posting, we still encourage you to apply to ensure that your application receives a review from our team. We understand that a resume can only showcase so much during the applicant stage, so we've created prompts in the application for you to share more about yourself. If you've made a career transition (or a few!), you’re self taught in a new role, or you have skills/experience you’d like to highlight, we want to hear more about what you could bring to the table.

AI in Recruitment At Loopio, we leverage artificial intelligence (AI) technology to enhance our recruitment process. These tools assist with tasks such as resume screening, drafting preliminary job descriptions, generating initial interview questions, and occasionally sourcing prospective candidates. However, AI is never used to make final hiring decisions; our use of AI serves to support repetitive and administrative tasks in order to streamline our hiring and recruitment workflows. We are committed to the responsible use of AI in our hiring practices, prioritizing both an improved candidate experience and operational efficiency. Our standardized hiring practices remain focused on reducing biases, with all key hiring decisions solely made by our team. We continuously review and refine our hiring practices to align with industry best practices and evolving legal guidelines

Loopio is an equal opportunity employer that is deeply committed to building equitable workplaces that are diverse and inclusive. We actively encourage candidates from all backgrounds and lifestyles to consider us as a future employer. Please contact a member of our Talent Experience team ([e-mail]) should you require accommodations at any point during our virtual interview processes.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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