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Staff Software Engineer
Rbc
Calgary, CAN
Onsite
Discovered 2 weeks ago
Machine learning model serving and lifecycle managementPythonApache KafkaReal-time streaming and event-driven architecturesAmazon SageMakerMLflow
Free
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Machine learning model serving and lifecycle managementPythonApache Kafka
Role Overview
Join RBC Borealis AI Platform as a Staff AI/ML Engineer responsible for the end-to-end lifecycle of production machine learning systems.
Own model operationalization at scale, with a focus on reliability, observability, and engineering excellence.
Work with machine learning researchers and large datasets across areas including reinforcement learning, unsupervised learning, and computer vision.
Key Skills for This Role
Machine learning model serving and lifecycle managementPythonApache KafkaReal-time streaming and event-driven architecturesAmazon SageMakerMLflow
Full Job Posting
About the role
Join RBC Borealis AI Platform as a Staff AI/ML Engineer responsible for the end-to-end lifecycle of production machine learning systems.
Own model operationalization at scale, with a focus on reliability, observability, and engineering excellence.
Work with machine learning researchers and large datasets across areas including reinforcement learning, unsupervised learning, and computer vision.
Responsibilities
- Design, build, and operate scalable ML model-serving infrastructure using SageMaker, MLflow, or equivalent platforms.
- Architect and maintain real-time data and feature pipelines using Kafka and streaming frameworks.
- Develop Python backend services that expose ML capabilities through reliable, documented APIs.
- Deploy and operate containerized ML workloads on OpenShift or Kubernetes, including autoscaling and rollout strategies.
- Build CI/CD pipelines with GitHub Actions or equivalent tools for model validation, packaging, and deployment.
- Implement observability with metrics, logs, and traces, and drive incident response and blameless post-mortems.
Required qualifications
- Production-proven experience with ML model serving and lifecycle management.
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