Position Details:

Title: Senior MLOps Consultant

Location: Toronto, ON (Remote Role)

Type: Full time

Duration: 12 Months with possible extension

Start Date: ASAP

:

Feature Engineering Pipeline Management

- Design and scale feature pipelines using Snowpark PythonSQL to transform raw data into productionready ML features
- Implement and manage the Snowflake Feature Store as a centralized governed repository for batch training and lowlatency online inference
- Optimize data ingestion and processing costs using Snowflakes elastic compute multicluster warehouses and search optimization services

Model Training Orchestration

- Establish scalable ML training infrastructure using Snowflake Notebooks and Container Runtimes CPUGPU instances without data egress
- Orchestrate endtoend ML workflows and retraining schedules using Snowflake Tasks and Streams
- Integrate opensource frameworks (ScikitLearn, PyTorch, XGBoost) into the Snowflake ecosystem via Snowpark ML

Model Deployment Serving

- Manage the Snowflake Model Registry for cataloging versioning metadata logging and lifecycle governance Development Staging Production
- Deploy models for batch and realtime inference using UserDefined Functions UDFs or containerized services
- Integrate LLMs and GenAI applications using Snowflake Cortex AI functions

MLOps Platform Setup Operations

- Design and build endtoend MLOps platform including CICD pipelines model registry experiment tracking and feature store
- Implement automated model training validation deployment and monitoring workflows




- Establish reusable ML pipeline templates and accelerators for development teams

CICD Automation Infrastructure

- Build automated CICD pipelines using Terraform for model testing validation and promotion
- Implement InfrastructureasCode IaC using Terraform to provision Snowflake resources securely and repeatably
- Enforce data and model governance through Snowflake's native security rowlevel security data masking RBAC

Monitoring Observability

- Deploy ML monitoring frameworks to track model performance data drift and prediction latency
- Design automated retraining loops triggered by accuracy drops or data distribution shifts
- Build operational dashboards using Streamlit in Snowflake for realtime model health visibility

Snowflake ML Standards Development

- Define and enforce ML engineering standards patterns and best practices within Snowflake
- Develop Snowflakenative ML workflows for feature engineering training and inference
- Manage Snowflake computewarehouse configurations optimized for ML workloads

ML Development Assistance

- Collaborate with data scientists to productionize models from prototype to productiongrade code
- Build shared libraries utilities and SDKs to accelerate model development
- Conduct code reviews and enforce coding and testing standards for ML codebases

Governance Documentation

- Establish model versioning lineage tracking and reproducibility standards
- Document platform architecture runbooks and onboarding guides
- Ensure compliance with RBC's data governance and security policies

Thanks & Regards

Cloudious LLC

📌 Senior MLOps Consultant (Toronto)
🏢 Cloudious
📍 Toronto