Overview
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
No Travel Required
Skills
vector database system
Integrate LLMs
Build and manage embedding pipelines
semantic search
OpenAI
Job Details
- Design, develop, and maintain high-performance vector database systems (e.g., Pinecone, Weaviate, Milvus, FAISS, Qdrant) for LLM-backed applications.
- Integrate LLMs (OpenAI, Claude, LLaMA, etc.) into data pipelines and AI solutions using RAG and embedding-based retrieval.
- Build and manage embedding pipelines (using OpenAI, HuggingFace, SentenceTransformers, etc.) for structured and unstructured data.
- Optimize vector search for latency, relevance, and scalability across large datasets.
- Collaborate with ML/AI engineers, data scientists, and product teams to deliver end-to-end solutions powered by AI.
- Monitor performance, ensure data security, and maintain high system availability.
- Evaluate and experiment with different vector indexing techniques (e.g., HNSW, IVF, PQ) and distance metrics (cosine, Euclidean, dot-product).
- Stay updated with the latest advancements in LLMs, vector databases, and semantic search.
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