Emerging Technology Solutions Architect – Machine Learning
Tasks
- Define end to end machine learning lifecycle architectures
- Define model governance and observability best practices
- Design machine learning architectures
- Enable implementation through technical leadership
- Establish reusable MLOps solution patterns
- Evaluate emerging machine learning technologies
- Evaluate vendor platforms for enterprise fit
- Guide enterprise adoption of machine learning
- Operationalize machine learning models at scale
- Provide model lifecycle management leadership
- Recommend architecture patterns for performance scalability security
- Translate technical concepts for stakeholders
Perks/Benefits
- 401k matching
- Adoption Assistance
- Disability insurance
- Healthcare benefits
- Life insurance
- Long-term disability
- Paid Holidays
- Paid vacation
- Parental leave
- Short-term disability
Skills/Tech-stack
AWS SageMaker | Azure Machine Learning | Batch Scoring | CI/CD | Cloud Architecture | Databricks | Explainability | Feature Store | Kubeflow | MLOps | MLflow | Machine Learning | Machine Learning Pipeline | Model Governance | Model Monitoring | Model Serving | Model versioning | Observability | PyTorch | Real Time | Real-time Inference | Scikit-learn | Snowflake | Solution architecture | TensorFlow | XGBoost
Education
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