ML & Database Engineer (No Third Parties Please)
4 months, remote, $55-$60/hour, Start ASAP, 20 hours per week
ML & Database Engineer
Required AWS Service Skills:
• Amazon SageMaker (primary) SageMaker Canvas SageMaker Model Monitor Amazon RDS/PostgreSQL (advanced) AWS Glue (advanced) Amazon S3 AWS Lambda Amazon CloudWatch
Required Technical Skills:
• Python (advanced) Machine Learning Feature Engineering ETL Pipelines SQL (advanced) Database Administration Database Design Batch Processing Data Validation Model Training Terraform
Required Soft Skills:
• Analytical Thinking Technical Documentation Knowledge Transfer Adaptability Team Collaboration
Primary Responsibilities:
• Design and implement database schemas and data models
• Configure and optimize PostgreSQL database instances
• Develop advanced ETL processes using AWS Glue
• Implement SageMaker Canvas environment for model exploration
• Design and develop machine learning models for deer movement prediction
• Create validation framework with accuracy metrics
• Implement SageMaker training pipeline for prediction models
• Configure distributed training and spot instance optimization
• Set up SageMaker batch transform jobs for nightly inference
• Develop database monitoring, backup and recovery procedures
• Implement data integration between application components and ML pipeline
• Assist with performance optimization and query tuning
• Develop data quality validation procedures
• Implement model drift detection and retraining mechanism
4 months, remote, $55-$60/hour, Start ASAP, 20 hours per week
ML & Database Engineer
Required AWS Service Skills:
• Amazon SageMaker (primary) SageMaker Canvas SageMaker Model Monitor Amazon RDS/PostgreSQL (advanced) AWS Glue (advanced) Amazon S3 AWS Lambda Amazon CloudWatch
Required Technical Skills:
• Python (advanced) Machine Learning Feature Engineering ETL Pipelines SQL (advanced) Database Administration Database Design Batch Processing Data Validation Model Training Terraform
Required Soft Skills:
• Analytical Thinking Technical Documentation Knowledge Transfer Adaptability Team Collaboration
Primary Responsibilities:
• Design and implement database schemas and data models
• Configure and optimize PostgreSQL database instances
• Develop advanced ETL processes using AWS Glue
• Implement SageMaker Canvas environment for model exploration
• Design and develop machine learning models for deer movement prediction
• Create validation framework with accuracy metrics
• Implement SageMaker training pipeline for prediction models
• Configure distributed training and spot instance optimization
• Set up SageMaker batch transform jobs for nightly inference
• Develop database monitoring, backup and recovery procedures
• Implement data integration between application components and ML pipeline
• Assist with performance optimization and query tuning
• Develop data quality validation procedures
• Implement model drift detection and retraining mechanism
