AI Data Platform Engineer
Tasks
- Build AI data lifecycle management automation and governance
- Build AI ready datasets with ground truth creation curation and annotation
- Collaborate with AI ML and software teams to deliver production data solutions
- Create observability and monitoring for data pipelines
- Design and build AI data platforms
- Develop data ingestion transformation and publishing pipelines
- Implement RAG pipelines embedding workflows and vector database integrations
- Implement data quality frameworks validation and evaluation metrics
- Maintain AI data platforms services and APIs
- Manage dataset versioning metadata and lineage
- Optimize scalability reliability performance security and cost
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Apache Airflow | Apache Iceberg | Apache Spark | Azure | CI/CD | Cloud Computing | Cloud platform | Data Governance | Data Lakehouse | Data Lineage | Data Quality | Data Validation | Delta Lake | Distributed Systems | Docker | Embeddings | Google Cloud | Google Cloud Platform | Infrastructure as Code | Java | Kafka | Knowledge graphs | Kubeflow | Kubernetes | MLflow | Metadata Management | Microservices | Observability | Pandas | PySpark | Python | Ray | Retrieval-Augmented Generation | SQL | Scala | Vector Database | Vector Search | “as-code”
Education
Regions
Countries
States
Cities
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