Role: Senior Machine Learning Engineer (Cloud & Data Platform)
Duration: Long Term
Location: Montreal, Canada- Hybrid

We are seeking a highly capable Senior Machine Learning Engineer to support the modernization of enterprise analytics and modeling platforms. This role focuses on migrating and transforming legacy data and machine learning workflows into scalable, cloud-native architectures while improving performance, reliability, and engineering standards.
The ideal candidate combines strong ML engineering expertise with deep experience in distributed data processing and cloud data platforms.


Responsibilities
🔹 Machine Learning Engineering
Design, develop, and deploy scalable machine learning models using modern frameworks (e.g., PyTorch)
Re-engineer and optimize legacy models into efficient, production-grade implementations
Improve model performance, scalability, and reproducibility
Support model validation, benchmarking, and certification processes
Ensure full traceability and documentation of model logic and outputs


🔹 Data Platform & Pipeline Engineering
Design and optimize distributed data pipelines using Spark-based platforms (e.g., Databricks)
Build and refactor ETL/ELT workflows for performance and scalability
Implement data models within modern cloud data warehouses (e.g., Snowflake)
Apply best practices for cloud-native data architecture
Standardize reusable utilities and frameworks for analytics workflows


🔹 Cloud Migration & Modernization
Participate in migration of on-prem or legacy analytics platforms to cloud ecosystems
Refactor existing codebases to align with modern engineering and DevOps standards
Leverage cloud compute capabilities (including GPU acceleration where applicable)
Support scheduling and orchestration of data and ML workflows


🔹 Testing, Validation & Governance
Conduct rigorous testing and validation to ensure data and model accuracy
Perform parallel runs and benchmarking when modernizing systems
Collaborate with governance, risk, and compliance stakeholders
Maintain high standards of documentation and reproducibility

All your information will be kept confidential according to EEO guidelines.