AI Data Infrastructure Engineer
Tasks
- Build evaluation dataset construction pipelines with integrity controls
- Build high throughput data loading systems
- Build ingestion systems for text image audio video and structured signals
- Design and operate large scale AI data pipelines
- Design storage architectures across data tiers
- Develop dataset versioning lineage and provenance tracking
- Document data systems schemas and operational procedures
- Drive observability of data quality drift and pipeline health
- Implement data cleaning deduplication filtering and quality assurance
- Implement data privacy redaction and consent enforcement
- Implement labeling workflows active learning and human in the loop improvement
- Optimize cost and performance with compression format selection and caching
Perks/Benefits
Skills/Tech-stack
Apache Beam | Apache Spark | CI/CD | Caching | Code review | Compression | Data Governance | Data Ingestion | Data Lineage | Data Modeling | Data Privacy | Data Quality | Data Storage | Data redaction | Data storage formats | Dataset versioning | Distributed Systems | Java | Machine Learning | Python | Ray | Scala | Storage Architecture | Storage Formats | Testing
Education
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