AI Data Engineer
Tasks
- Build evaluation dataset construction pipelines
- Build high throughput data loading systems for training
- Build ingestion systems for multimodal data
- Collaborate with ML researchers and engineers
- Design data pipelines for AI training and evaluation
- Design storage architectures for cost latency and throughput
- Develop dataset versioning and lineage tracking
- Document data systems schemas and procedures
- Drive observability for data quality drift and pipeline health
- Implement data cleaning and quality assurance at scale
- Implement data privacy redaction and consent enforcement
- Implement labeling workflows and active learning
- Optimize cost and performance using compression and caching
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Beam | Apache Spark | CI/CD | Compression | Data Consent | Data Drift | Data Lineage | Data Modeling | Data Observability | Data Privacy | Data Quality | Data caching | Data loading | Data redaction | Dataset versioning | Distributed Systems | High Throughput | High Throughput Data Loading | High-throughput data | Java | Machine Learning | Machine Learning Pipelines | Multimodal Data | Python | Ray | Scala | Storage Architecture
Education
Roles
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