Principal Engineer Software (Machine Learning)
Tasks
- Architect and lead full machine learning lifecycle from training to production deployment and real time inference
- Build and maintain automated resilient CI CD and monitoring systems for backend and machine learning components
- Design and deliver scalable cloud security architecture through hands on coding
- Design and implement cloud security solutions for backend infrastructure and ML model challenges
- Establish best practices for model versioning reproducibility auditing and compliance
- Evaluate and integrate MLOps tools and frameworks
- Manage and optimize ML infrastructure and pipelines to improve performance and reduce operational costs
- Provide technical leadership for end to end solution delivery
Perks/Benefits
Skills/Tech-stack
Amazon Web Services | Apache Flink | CI/CD | Cloud platform | CloudFormation | Compliance | Continuous Delivery | Continuous integration | Data Privacy | Distributed Systems | Docker | Go | Google Cloud | Google Cloud Platform | Infrastructure as Code | Java | Kafka | Kubernetes | MLOps | Machine Learning | Microsoft Azure | Model Deployment | Monitoring | PyTorch | Python | Streaming | TensorFlow | Terraform | Web Services | “as-code”
Education
Regions
Countries
States
Cities
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