AI Data Engineer
Tasks
- Build high throughput data loading systems to maximize GPU utilization
- Build ingestion systems for text image audio video structured data
- Collaborate with ML researchers and engineers on data needs
- Construct evaluation datasets with integrity and contamination controls
- Design 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 for 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 using compression formats and caching
Perks/Benefits
- N/A
Skills/Tech-stack
Active Learning | Apache Beam | Apache Spark | CI/CD | Caching | Code review | Compression | Data Lineage | Data Modeling | Data Privacy | Data Quality | Data Versioning | Data loading | Data redaction | Dataset evaluation | Distributed Systems | GPU Utilization | High Throughput | High Throughput Data Loading | High-throughput data | Human-in-the-loop | Java | Multimodal Data | Python | Ray | Scala | Storage Architecture | Testing | The Loop
Education
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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