Data Engineer (5+)
emagine
|
16 days ago
|
Remote
Main Responsibilities
- Build and deploy GraphRAG solutions integrating knowledge graphs (e.g., Neo4j) and vector databases (e.g., Weaviate).
- Develop Hybrid Retrieval systems using FAISS/Milvus + BM25.
- Fine-tune LLMs (GPT, LLaMA, Falcon) using LoRA/PEFT.
- Build scalable GenAI pipelines using Hugging Face, LangChain, Weaviate, and OpenAI APIs.
- Implement Weaviate’s Ignition Framework for enterprise-grade RAG (mandatory).
- Deploy solutions on AWS/GCP/Azure with strong MLOps practices.
- Evaluate and optimize retrieval and generation performance.
- Work closely with engineering and product teams to deliver production AI systems.
- Maintain strong documentation, monitoring, and optimization of AI pipelines.
Key Requirements
- 5–8+ years of hands-on AI/ML engineering with production deployments.
- Strong NLP + LLM experience:
- LoRA/PEFT fine-tuning
- Prompt engineering
- Embeddings & retrieval optimization
- Practical experience with GraphRAG, knowledge graphs, and Neo4j.
- Mandatory: Experience with Weaviate’s Ignition Framework.
- Strong Python; PyTorch/TensorFlow proficiency.
- Experience with Hybrid Retrieval (FAISS, Milvus, Pinecone + BM25).
- Solid knowledge of vector databases and RAG pipelines.
- Real GenAI product experience (not academic).
- Strong English communication; ability to work with partial Poland timezone coverage
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