Senior MLOps Engineer | Ingénieur·e MLOps senior
Jesta I.S.29 days ago
Remote, Canada or Montréal, CanadaSenior
Responsibilities
- Build and automate ML pipelines for data preparation, training, inference, monitoring, and retraining.
- Develop production data flows across Oracle ERP, Snowflake, AWS, and Azure.
- Create reusable Kedro pipelines and manage scalable workloads with AWS Batch, EKS, Karpenter, Kueue, and Fargate.
- Implement MLflow experiment tracking, model versioning, lineage, quality gates, staged promotion, and rollback.
- Create reproducible run manifests, validate prediction completeness, and support recovery from partial runs.
- Provision secure, multi-tenant cloud infrastructure using Terraform or OpenTofu.
- Implement CI/CD workflows with Azure DevOps and GitHub Actions, including testing, scanning, immutable images, and rollback strategies.
- Build observability for run success, completeness, freshness, duration, drift, failures, and infrastructure cost.
- Maintain Dockerized, Kubernetes-native environments using ECR and EKS with appropriately sized resources.
- Deploy secure React and Python ML applications across AWS and Azure using private networking, MFA, RBAC, encryption, and least-privilege access.
- Collaborate with Data Scientists and Product stakeholders to operationalize models, improve performance, and address reliability gaps.
Requirements
- Bachelor’s or master’s degree in Computer Science, Machine Learning, or a related field.
- At least 5 years of full-time professional experience, excluding internships and academic training, in ML Engineering, MLOps, or data-pipeline development.
- Seven or more years of relevant professional experience is preferred.
- Proven ability to design, build, and automate production-scale, end-to-end ML pipelines in cloud environments.
- Strong Python and SQL skills, including complex queries against large datasets.
- Hands-on experience integrating Oracle and Snowflake with production ML systems.
- Proficiency with Terraform or equivalent Infrastructure as Code tooling.
- Experience with containerized application deployment, CI/CD, workflow orchestration, Kubernetes/EKS, and cloud-native infrastructure.
- Experience with MLflow or equivalent MLOps tooling.
- Understanding of model lifecycle practices including versioning, lineage, quality validation, staged promotion, monitoring, and rollback.
- Experience with cloud platforms, preferably AWS and Azure.
- Strong ownership, analytical problem-solving, performance focus, collaboration, adaptability, and attention to automation, observability, reliability, and responsible data handling.
Benefits
- Hybrid work model requiring two days per week in the Montreal office.
- Remote work is possible for exceptional candidates.
Tech Stack
AWSAzureDockerGitHub ActionsGrafanaJavaScriptKubernetesLightGBMMLflowPandasPrometheusPythonReactSnowflakeSQLTerraformXGBoost
Categories
About Jesta I.S.
Jesta I.S. builds enterprise software for retailers and wholesalers in apparel, footwear, and hard goods. Its Vision suites provide merchandising ERP, point of sale, order management, and supply chain management as integrated platforms for unified commerce. The company is privately held, founded in 1968, and headquartered in Montreal, serving global brands seeking end-to-end retail and supply chain capabilities.