AI Platform Engineer
Tasks
- Build automated CI CD systems
- Design and implement MLOps pipelines
- Design data pipelines and feature stores
- Develop ML inference infrastructure
- Implement model monitoring, drift detection, and retraining
- Implement security and compliance controls for ML systems and data
- Optimize ML infrastructure performance cost and reliability
- Productionize research models
Perks/Benefits
Skills/Tech-stack
API Development | Airflow | Automated retraining | CI/CD | Cloud Platforms | Databases | Docker | Drift Detection | Infrastructure as Code | Kafka | Kubernetes | ML Model Serving | MLOps | Model Drift | Model Drift Detection | Model Serving | Monitoring | Observability | PyTorch | Python | Scikit-learn | Spark | TensorFlow | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Platform Engineer | Engineer | MLOps Engineer | Platform Engineer
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