Remote Senior MLOps Engineer: ML Lifecycle Orchestrator

KData AI; United States; A distancia; CAD 110.000 - 180.000; Jornada completa

Descripción de la vacante

KData AI is seeking a Senior MLOps Engineer to lead the industrialization and orchestration of the full ML lifecycle. You will design, build, and maintain scalable ML pipelines that support deployment, monitoring, drift management, and governance across production systems.

You will bridge Data Science, Data Engineering, and DevOps, leveraging Snowflake, dbt, Terraform, and GitOps practices to ensure reproducible features, secure access, and robust CI/CD pipelines in a remote, Canada-based setup.

Formación

• 5+ years of hands-on experience in MLOps, Data Engineering, or DevOps.
• Proven experience with Snowflake ecosystem for ML workloads.
• Automation of CI/CD pipelines and infrastructure via IaC tools.
• Experience with dbt data transformations and data quality checks.
• Solid ML observability and drift detection experience.
• Strong governance, versioning, and RBAC practices.

Responsabilidades

• Architect end-to-end MLOps solutions for deployment, scaling and retraining pipelines.
• Establish model governance and lineage with metadata tracking.
• Build model monitoring for performance, drift, and alerts.
• Implement centralized Feature Stores for reproducible features.
• Use IaC and GitOps to automate deployments and security controls.
• Integrate dbt with ML observability to ensure data/model integrity.

Conocimientos

Snowflake ML

ML Monitoring

Data Transformation

Infra as Code

RBAC Governance

Herramientas

dbt

Terraform

Jenkins

GitOps

Descripción del empleo

KData AI is seeking a Senior MLOps Engineer to lead the industrialization and orchestration of the full ML lifecycle. You will design, build, and maintain scalable ML pipelines that support deployment, monitoring, drift management, and governance across production systems.

You will bridge Data Science, Data Engineering, and DevOps, leveraging Snowflake, dbt, Terraform, and GitOps practices to ensure reproducible features, secure access, and robust CI/CD pipelines in a remote, Canada-based setup.