AI/ML Architect
Tasks
- Build and deploy production machine learning models
- Coordinate with multiple development teams
- Design end-to-end ML architectures
- Estimate ML opportunities and support proposals and RFP responses
- Implement MLOps practices
- Lead and mentor ML engineers and data scientists
- Monitor models and detect drift
- Optimize model performance and resolve degradation
- Perform code reviews for ML pipelines
- Provide technical authority for client workshops and pre sales
- Translate client problems into ML solutions
- Work in agile environment and follow scrum
Perks/Benefits
- N/A
Skills/Tech-stack
Amazon Web Services | Anomaly Detection | Azure | Cloud platform | Data Ingestion | Databricks | Drift Detection | Feature Engineering | Git | Google Cloud | Google Cloud Platform | Imbalanced classification | LightGBM | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model Training | PyTorch | Python | REST API | Retraining Pipelines | SQL | Scikit-learn | Series analysis | Spark | Supervised Learning | TensorFlow | Time Series | Time Series Analysis | Web Services | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI/ML Architect | Architect | Engineer | Learning Engineer | ML Architect | Machine Learning Engineer
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