Data & ML Engineer
Tasks
- Bind generated text to cited source records
- Build data model and entity graph
- Build secure data ingestion transformation validation and publishing
- Calibrate scores and define threshold policy
- Design abstention policy for uncertain cases
- Design prompts and output schemas
- Detect source drift
- Develop relevance and priority models
- Establish data provenance and lineage
- Generate synthetic data
- Implement embeddings vector storage and retrieval
- Implement probabilistic record matching
- Implement quality checks schema validation lineage capture and audit logging
- Instrument telemetry
- Integrate language models via managed service
- Maintain audit trail for recommendations overrides and model versions
- Manage model packaging serving versioning and rollback
- Perform deduplication and known record suppression
- Perform feature engineering and error analysis
- Submit changes through gated release process
Perks/Benefits
- Employer-paid health insurance
- Flexible work environment
- Fully remote
- Paid parental leave
- Unlimited PTO
Skills/Tech-stack
AWS Glue | Airflow | Apache Kafka | Apache Spark | Audit Logging | Calibration | Cost-sensitive learning | DBT | Data Generation | Data Lineage | Embeddings | Feature Engineering | Graph Algorithms | Graph Modeling | Kafka | Language Models | Large Language Models | Machine Learning | Nifi | PGVector | PostgreSQL | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Schema Validation | Scikit-learn | Synthetic Data Generation | Synthetic data | Telemetry | Thresholding | Vector Databases | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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