ML Platform Engineer (Contractor)
Tasks
- Build and maintain MLOps automation
- Build and maintain data pipelines for ingestion and transformation
- Design and implement CI CD for models and pipelines
- Design and maintain feature store or feature platform
- Detect feature drift and data quality issues
- Enforce secure data handling access control and audit compliance
- Expose governed datasets features and APIs
- Implement experiment tracking and reproducible training
- Maintain platform documentation and engineering standards
- Manage model deployment and serving infrastructure
- Orchestrate training and experimentation jobs
- Set up ML observability and monitoring
Perks/Benefits
- Course access
- Performance bonuses
- Professional development budget
- Promotions
- Social activities
- Teambuilding events
- Training opportunities
Skills/Tech-stack
Airflow | Alerting | Apache Spark | Artifact versioning | Bias detection | BigQuery | CI/CD | Cloud Build | Cloud Run | Composer | Dagster | Data Quality | Docker | Drift Detection | Experiment tracking | Feature Drift | Feature Drift Detection | Feature Store | GitHub Actions | Hyperparameter Tuning | Incident Response | MLflow | Model Monitoring | Model Registry | Python | Reproducible training | SQL | Terraform | Vertex Experiments
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Engineer | ML Platform Engineer | MLOps Engineer | Platform Engineer
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