Description:

Loopio is seeking a skilled and motivated MLOps Engineer to help scale and productionize machine learning systems for their intelligent product features.
The role involves close collaboration with ML Engineers, Data Scientists, and Backend Engineers to build the necessary pipelines, infrastructure, and tooling for delivering high-impact ML models.
Responsibilities include building and maintaining robust ML pipelines for training, evaluation, and deployment, automating workflows, and supporting reproducible experimentation.
The engineer will package and deploy models into production environments using tools like Docker, Kubernetes, and SageMaker, and build REST/gRPC services for real-time or batch model serving.
The role also includes implementing systems to monitor model health in production, detecting drift, and contributing to alerting and dashboarding.
The engineer will work within CI/CD systems to support model validation, promotion, and rollback, and help build automated workflows for model deployment.
Collaboration with ML Engineers and Data Scientists is essential to bring ML systems into production, improve developer experience, and debug operational issues.
The position is remote-first, with flexible co-working locations available in Ontario and British Columbia, and encourages asynchronous collaboration across global teams.

Requirements:

Candidates must have 2+ years of experience in ML operations, ML engineering, or related infrastructure roles, with familiarity in deploying ML models and automating ML pipelines.
Comfort with AWS (or similar cloud environments), Docker, and Kubernetes is required, along with experience in workflow orchestration tools like Airflow, Dagster, or Kubeflow being a plus.
Strong Python development skills and a solid understanding of software engineering practices, including testing, logging, version control, and code review, are necessary.
Experience with model deployment and monitoring tools such as MLflow, SageMaker, TensorFlow Serving, or TorchServe is required, with bonus points for hands-on experience in implementing model monitoring or drift detection systems.
Candidates should be comfortable working cross-functionally with both technical and non-technical stakeholders, demonstrating curiosity, communication skills, and openness to feedback.
A growth mindset is essential, with a desire to learn about ML systems in production and a proactive approach to building effective solutions.

Employees receive ongoing feedback and regular 1-on-1s from their managers to support their development.
There is a dedicated professional mastery allowance for learning support, encouraging experimentation and innovative thinking.
A wide range of health and wellness benefits is provided to support physical and mental well-being from day one.
Employees are equipped to work remotely with a MacBook laptop, a monthly phone and internet subsidy, and a work-from-home budget.
The company fosters a supportive culture with opportunities for connections in a remote-first environment, including townhalls and quarterly celebrations.
Employees can participate in four active Employee Resource Groups for learning and connection throughout the year.
Loopio is recognized as an award-winning workplace, offering the opportunity to make a significant impact on the business.