AI Pipeline Engineer
Tasks
- Build evaluation dataset construction with integrity and contamination controls
- Build high throughput data loading systems for training jobs
- Build ingestion systems for multimodal data
- Design and operate large scale AI data pipelines
- 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 with compression formats and caching
Perks/Benefits
Skills/Tech-stack
Apache Beam | Apache Spark | CI/CD | Code review | Data Deduplication | Data Lineage | Data Modeling | Data Privacy | Data Quality | Data cleaning | Data loading | Data reproducibility | Dataset versioning | Distributed Systems | High Throughput | High Throughput Data Loading | High-throughput data | Java | Python | Ray | Rédaction | Scala | Storage Optimization | Testing
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Pipeline Engineer | Data Engineer | Engineer | Pipeline Engineer
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