Senior Machine Learning Engineer (Toronto)
Tasks
- Build MLOps infrastructure for training deployment and monitoring
- Conduct code reviews and system design
- Design machine learning pipelines for real time ad decisioning
- Implement experimentation systems
- Integrate data with partners
- Optimize outcomes using A B testing and multi armed bandits
- Translate business goals into model solutions
- Tune performance and latency for production machine learning systems
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Airflow | Apache Spark | B testing | Cloud Native | Cloud-native development | Data Architectures | Evaluation metrics | Experimentation | Kubernetes | Latency optimization | MLOps | MLflow | Machine Learning | Model Deployment | Model Monitoring | Multi-Armed Bandits | Native Development | Performance Tuning | PyTorch | Python | Real Time | Real-time Inference | Snowflake | Streaming Data | Streaming data architectures | TensorFlow
Education
N/A
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