Data & ML Engineer
Tasks
- Add quality checks and schema validation
- Bind generated text to cited sources
- Build data ingestion pipelines
- Calibrate scoring and define thresholds
- Capture lineage and audit logging
- Deduplicate and suppress known records
- Design entity graph data model
- Design prompts and output schemas
- Detect source data drift
- Develop relevance and priority models
- Establish data provenance tracking
- Generate synthetic representative test data
- Implement abstention policy
- Implement embeddings and vector retrieval
- Implement gated release deployment process
- Implement probabilistic record matching
- Implement secure data transformation and validation
- Instrument telemetry and monitoring
- Integrate language models via managed service
- Package and serve machine learning models
- Perform feature engineering and error analysis
Perks/Benefits
- Career growth opportunity
- Employer-paid health insurance
- Fully remote
- Paid parental leave
- Unlimited PTO
Skills/Tech-stack
AWS Glue | Abstention Policy | Apache Airflow | Apache Kafka | Apache NiFi | Apache Spark | Audit Logging | DBT | Data Engineering | Data Generation | Data Modeling | Embeddings | Entity Resolution | Error Analysis | Feature Engineering | Graph Databases | Kafka | Language Models | Machine Learning | Model calibration | PGVector | PostgreSQL | Probabilistic matching | Prompt engineering | PyTorch | Python | Record Linkage | Retrieval-Augmented Generation | SQL | Schema Validation | Scikit-learn | Spark | Synthetic Data Generation | Synthetic data | Telemetry | Thresholding | Vector Databases | XGBoost
Education
N/A
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