Data Engineer
- Джерело:
- djinni.co
Що робити
- Design and build ETL/ELT pipelines for large volumes of unstructured data using orchestrators such as Temporal, Prefect, Celery, or Airflow, along with distributed processing engines like Ray and Spark.
- Automate AI-related tasks including text extraction, summarization, OCR, named entity recognition, and embedding generation using various self-hosted models, including some developed in-house.
- Design data schemas and manage storage across multiple systems, including relational databases (PostgreSQL), NoSQL databases (Elasticsearch, Mongodb), vector search engines (Qdrant, Milvus), and graph databases (Neo4j).
- Set up and maintain messaging queues for distributed data processing using tools such as Kafka, RabbitMQ.
- Develop custom Python tools and logic to ensure high throughput, reliability, and fault tolerance in data pipelines.
Що пропонуємо
- Make a Real Impact: Our systems have already been validated in real-world, nation-state level operations.
- Right Place, Right Time: Work at the intersection of AI, large-scale data processing, and cybersecurity.
- Military Deferment: Available for full-time employees.
- Flexible Schedule: Remote-friendly environment focused on results rather than rigid hours.
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