Machine Learning Engineer (Canada)
Core
Designing, deploying, and maintaining scalable machine learning systems and production data pipelines for Fortune 100 clients.
Role type
Machine Learning Engineer
Builds
Scalable ML systems, production data pipelines, and reusable code libraries
Domain
Advanced analytics consulting, Big Data, Cloud-native ML
Deliverable
production ML models
Required skills
Python, Spark, Hadoop, Docker, SQL, statistical tools, relational databases, model evaluation, experimental design, test-driven development, cloud environment experience
Preferred skills
ML frameworks (Scikit-learn, Tensorflow, Keras), MLflow, Airflow, Kubernetes, cloud-native MLaaS (AWS SageMaker, AzureML, Google AI platform)
Technologies
Python, Spark, Hadoop, Docker, PyTest/Nose, AWS SageMaker, AzureML, Google AI platform, MLflow, Airflow, Kubernetes, Scikit-learn, Tensorflow, Keras
Responsibilities
Deploy, execute, validate, monitor, and improve data science solutions; build reusable production data pipelines; manage infrastructure and data pipelines for ML solutions; troubleshoot production ML model issues and recommend retraining; collaborate with Data Engineers and Data Scientists on pipelines and experiments
Seniority
Mid-Senior, hands-on IC