G01 - Systems Engineer
Singapore, Singapore, Singapore
SGD 69K-179K (estimate) Mid-level Full Time
Tasks
- Automate data pipelines and ML workflows with MLOps
- Build proof of concepts for feasibility and performance
- Deploy AI ML models across cloud and edge
- Deploy and manage video analytics systems
- Design cloud application and edge infrastructure for AI ML
- Develop CI CD pipelines for model training testing deployment
- Ensure security, compliance, and data governance
- Ensure system reliability and SLA adherence
- Implement logging, monitoring, and alerting
- Integrate AI solutions with existing infrastructure
- Integrate solutions with REST APIs databases and messaging systems
- Manage edge infrastructure with containerization and monitoring
- Manage model retraining pipelines and version control
- Monitor system health and respond to incidents
- Optimize system performance latency throughput and GPU utilization
- Provide technical support across infrastructure and AI ML systems
- Translate business requirements into system designs
- Troubleshoot and maintain infrastructure and deployed systems
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Alerting | CI/CD | Computer Vision | Database | Distributed Systems | Docker | EC2 | ECS | EKS | ETL | Edge AI | Git | IAM | Infrastructure as Code | IoT | Java | Kubernetes | Lambda | Logging | MLOps | Monitoring | NVIDIA Jetson | OpenCV | PyTorch | Python | REST API | S3 | SageMaker | TensorFlow | TypeScript | VPC | “as-code”
Education
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