ML Platform Engineer (Contractor)
Tasks
- Build and maintain MLOps automation
- Build data pipelines for ingestion transformation and export
- Build training and experimentation infrastructure
- Develop feature store and feature platform layer
- Enforce secure data handling and access controls
- Ensure point in time feature correctness
- Implement incident response workflows
- Implement model CI CD pipelines
- Maintain ML engineering documentation and standards
- Manage deployment strategies
- Monitor ML data quality and drift
- Monitor model performance and bias
- Operate model serving infrastructure
- Orchestrate training jobs and compute
- Provide governed datasets features and APIs
- Track experiments and manage hyperparameters
Perks/Benefits
- MyPOS Academy upskilling
- Promotions and performance bonuses
- Training budget
- Unlimited courses access
Skills/Tech-stack
AWS | Airflow | Bias detection | BigQuery | CI/CD | Cloud Build | Cloud platform | Composer | Dagster | Data Drift | Data Drift Detection | Data Quality | Docker | Drift Detection | Feature Store | GitHub Actions | Google Cloud | Google Cloud Platform | Incident Response | Kubernetes | MLOps | MLflow | Machine Learning | Microsoft Azure | Model Monitoring | Model Serving | Observability | Python | SQL | Spark | Terraform | Vertex Experiments
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
Engineer | ML Platform Engineer | MLOps Engineer | Platform Engineer
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