AI Data Engineer
Tasks
- Build evaluation dataset construction pipelines with integrity controls
- Build high throughput data loading systems for accelerator based training
- Build ingestion systems for multimodal data
- Collaborate with ML teams on data systems for model development
- Design and operate large scale data pipelines for AI training and evaluation
- Design storage architectures for cost throughput and latency
- 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 and active learning pipelines
- Optimize cost and performance using compression formats and caching
Perks/Benefits
Skills/Tech-stack
Active Learning | Apache Beam | CI/CD | Caching | Code review | Data Compression | Data Lineage | Data Modeling | Data Privacy | Data Quality | Data loading | Data provenance | Dataset versioning | Distributed Systems | High Throughput | High Throughput Data Loading | High-throughput data | Human-in-the-loop | JVM | Labeling | Python | Ray | Spark | Testing | The Loop
Education
Roles
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