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What You’ll Do
- Build and support data ingestion & ETL (APIs/DBs/files), parsing, validation, and transformations;
- Contribute to domain modeling & schema design (entities/relationships, migrations/versioning support);
- Implement LLM/NLP pipelines (structured extraction, classification, summarization) with basic monitoring and QA;
- Help build RAG backends and integrate assistants with apps (retrieval, grounding, citations);
- Develop/extend backend APIs & metadata stores consumed by internal tools and UIs;
- Support AWS/MLOps/DevOps work (deployments, CI/CD, logging/monitoring, runbooks) with mentorship.
- Python, SQL, ETL/pipeline fundamentals;
- Familiarity with ML/DS basics;
- Hands-on AWS exposure;
- Familiarity with LLMs (prompting, structured outputs, embeddings/RAG basics);
- High motivation to learn and work on AI projects.
- Airflow/Dagster/Prefect, Docker, Terraform/CDK;
- Vector DB/search (pgvector/OpenSearch/Pinecone/etc.);
- Basic UI/internal tooling (React/Streamlit).
- Professional and career growth promotion;
- Competitive salary;
- Paid vacations and sick leaves;
- Internal Medical Program;
- Flexible working hours;
- Regular corporate social activities;
- Regular technical training at our office;
- English courses;
- Gym, etc.
Key Skills
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