AI Operations Engineer
Tasks
- Build evaluation dataset construction with integrity and contamination controls
- Build high throughput data loading systems for GPU utilization
- Build ingestion systems for text image audio video and structured signals
- Design and operate large scale data pipelines for AI training and evaluation
- 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 using compression formats and caching
Perks/Benefits
Skills/Tech-stack
Apache Beam | Apache Spark | CI/CD | Code review | Data Lineage | Data Modeling | Data Privacy | Data Quality | Data loading | Data quality assurance | Data redaction | Dataset versioning | Distributed Systems | GPU Utilization | High Throughput | High Throughput Data Loading | High-throughput data | Java | Provenance tracking | Python | Quality Assurance | Ray | Storage Formats | Testing
Education
Roles
AI | AI Operations Engineer | Data Engineer | Engineer | Operations Engineer
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