Semantic Backend Engineer (Contract, Remote)

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Overview

INKHUB is ingesting 10 million raw PDFs to build the Internet's richest catalog of marketing-grade B2B content — tagged, summarized, and searchable by topic, company, or intent.

What You’ll Do

• Own the ETL pipeline from raw PDFs (S3-ingested) to structured resources.
• Finalize our summarization and classification flow using open-source models with GPT-4o fallback.
• Apply filtering logic (e.g., 3‑year age, page count) to enforce resource quality.
• Map each asset to the specific topic taxonomy (10+ per topic across ~9 topics).
• Generate dense embeddings using sentence‑transformers.
• Load and query embeddings using Milvus or pgvector.
• Implement “freshness” logic to identify and index only new or updated content based on file diffing, crawl timestamp, or document hash.
• Build a QA / eval harness : format compliance, , drift monitoring.
• Expose / v1 / semantic‑search via FastAPI, with filtering and rank fusion.
• Collaborate closely with our Tech Lead on UX integration and snippet generation.

Your Toolbox

Python, PyTorch, sentence‑transformers, OpenAI APIs, or similar pretrained LLMs. FastAPI, Milvus or pgvector, PyPDF / Tika, Airflow or Lambda for orchestration. Docker, GPU scheduling, Athena / Redshift SQL.

You Might Be a Fit If

Why This Role Matters

Your models decide what gets found, how it's tagged, and which content and companies stand out. You’ll help define what “relevance” and “freshness” mean for over a million resources and 50+ company pages and make sure INKHUB stays ahead of the curve.

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