Senior AI/ML Applications Architect
Tasks
- Architect scalable AI/ML solutions
- Build data and MLOps pipelines
- Deploy models to edge and cloud
- Deploy on edge platforms
- Design Generative AI applications
- Develop and demo proof-of-concepts
- Develop modular microservices architecture
- Establish AI ML architectural standards
- Evaluate and recommend emerging AI/ML technologies
- Implement CI/CD pipelines
- Implement containerization and orchestration
- Integrate AI/ML into existing platforms
- Monitor AI ML research trends
- Optimize model performance in production
Perks/Benefits
- N/A
Skills/Tech-stack
API first | AWS SageMaker | Adversarial Networks | Auto Scaling | Azure ML | Azure ML Registry | Azure Machine Learning | C Sharp | C plus plus | CI/CD | Containerization | Data Pipelines | Data Quality | Dataiku | Diffusion Models | DigSilent | Docker | Edge Computing | Generative AI | Generative Adversarial Networks | Google Vertex | Google Vertex AI | GraphDB | Infrastructure as Code | IoT | Kubernetes | Language Models | Large Language Models | Load forecasting | MATLAB | MLOps | Machine Learning | Microservices | Model Deployment | Model Evaluation | Model Tuning | NoSQL | PSS/E | Power system | Power system simulation | Predictive Modeling | PyTorch | Python | R | SQL | Scikit-learn | Series analysis | Signal Processing | System simulation | TensorFlow | Time Series | Time Series Analysis | Vertex AI | “as-code”
Education
Roles
AI | AI/ML Architect | Applications Architect | Architect | ML Architect
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