Senior Staff AI Data Infrastructure/Pipeline Engineer
Tasks
- Build data cleaning and annotation quality inspection tools
- Build data management platform to support model training
- Build distributed data processing systems
- Build offline and real time data processing systems
- Collaborate with model training teams on requirements and implementation
- Design data closed loop pipelines
- Develop data mining toolchains for error case discovery
- Enable fast data retrieval for team collaboration
- Implement data lake ingestion platform
- Implement log event tracking and connected vehicle data ingestion
- Manage data version control data lineage and metadata
- Optimize data pipeline throughput and latency
- Perform data synchronization and data standardization
- Provide data as a service and data visualization
- Solve large scale transmission memory and I O bottlenecks
Perks/Benefits
Skills/Tech-stack
Apache Iceberg | Apache Kafka | Caching | Data Lake | Data Lineage | Data version control | Distributed Systems | Docker | ETL | Go | High Throughput | Iceberg | Java | Kubernetes | Lance | Low Latency | Metadata Management | MongoDB | MySQL | NoSQL | Performance Tuning | PostgreSQL | Pulsar | Python | RabbitMQ | Redis | Relational databases | Stream processing | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Data Infrastructure Engineer | AI Data Pipeline Engineer | Data Engineering | Data Engineering Manager | Data Infrastructure Engineer | Data Pipeline Engineer | Engineer | Engineering Manager | Infrastructure Engineer | Manager | Pipeline Engineer | Senior Staff AI Data Infrastructure Engineer | Staff AI Data Infrastructure Engineer
Regions
Countries
States
Cities
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