Software Engineers with MLOps Experience

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*This position is remote-first within Canada. To be eligible, you must be based in Canada and authorized to work here. Relocation assistance is not available.

As a Software Engineer on the Data Platform team, you will design and develop orchestration systems that enable real-time, offline, and batch workflows for AI, ML, and data workloads. You’ll work with cross-functional partners and internal product teams to deliver reliable, scalable, and easy-to-use infrastructure that accelerates model development and deployment.

The Client's Data Platform powers the machine learning, AI, and data services that enable intelligent experiences across the client's products. As a Software Engineer focused on MLOps, you’ll help build the unified orchestration layer that powers large-scale data and ML workflows across the client's company. Leveraging cutting-edge open source technologies such as Ray and Spark, you’ll design and implement scalable systems that enable teams to train models, analyze data, and deploy AI at scale with strong governance. This is an opportunity to shape the future of ML infrastructure and have a direct impact on the experiences used by millions of people every day.

• Design, implement, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring
• Build and optimize automated training, validation, and deployment workflows that support rapid experimentation and production releases
• Develop robust monitoring and alerting systems to ensure model performance, data quality, and system reliability
• Create self-service tools and platforms that enable ML teams to deploy and manage models independently
• Implement security and privacy controls throughout the ML lifecycle, ensuring compliance with client's high standards
• Collaborate with diverse teams including accessibility specialists to ensure ML tools are usable by team members with varying abilities
• Drive infrastructure cost optimization and resource efficiency across ML workloads
• Establish best practices for model governance, including versioning, rollback strategies, and A/B testing frameworks
• Build documentation and training materials that support teams with different technical backgrounds

• Experience designing, building, and maintaining ML infrastructure and deployment pipelines using containerization technologies (Docker, Kubernetes preferred) and cloud platforms (AWS, Azure, or GCP)
• Proficient coding skills in Python, Go, or Scala with experience in ML frameworks (TensorFlow, PyTorch)
• Strong experience with Infrastructure as Code (Terraform, CloudFormation) and CI/CD tools (Jenkins, GitLab CI, GitHub Actions)
• Proficiency in monitoring and observability tools (Prometheus, Grafana, ELK stack) for ML model performance and system health
• Experience with data pipeline orchestration tools (Airflow, Dagster) and streaming platforms (Kafka, Kinesis)
• Knowledge of ML model versioning, experiment tracking, and feature stores (MLflow, Weights & Biases, Feast)
• Experience with automated testing frameworks for ML systems, including data validation and model testing
• Understanding of security best practices for ML systems and data governance
• Excellent grasp of software engineering fundamentals and DevOps practices
• Proficient knowledge of Git and collaborative development workflows
• BS, MS in Computer Science, Software Engineering, Machine Learning, or equivalent degree with applicable experience
• 14+ years of professional experience
• 3+ years of experience in MLOps, DevOps, or related infrastructure roles
• Experience working in cross-functional teams and communicating technical concepts to diverse audiences

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At.Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.