Machine Learning Engineer
Tasks
- Build low latency prediction endpoints
- Champion unit testing containerization and version control
- Deploy and maintain scalable GCP based ML infrastructure
- Design and implement machine learning CI CD CT pipelines
- Implement automated monitoring and alerting for model drift
- Operationalize machine learning models to production
- Scale machine learning systems with high velocity
Perks/Benefits
- N/A
Skills/Tech-stack
AI Pipelines | AI Workbench | AI endpoints | Apache Kafka | Automated testing | Cloud Pub/Sub | Cloud platform | Continuous Delivery | Continuous Deployment | Continuous integration | Docker | Google Cloud | Google Cloud Platform | Google Cloud Pub/Sub | Google Kubernetes | Google Kubernetes Engine | Infrastructure as Code | Kubernetes | Kubernetes Engine | MLOps | Model Monitoring | Pub/Sub | Python | Terraform | Vertex AI | Vertex AI Endpoints | Vertex AI Workbench | Vertex AI pipelines | “as-code”
Education
N/A
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