Happy New Year from AU

  Location: Sydney, Australia (work across US/AU/EU time zones)
  Remote: Yes
  Willing to relocate: Open to short relocations; E-3 eligible for US. Also open to B2B contracting.
  Technologies: 

* Backend: Python, FastAPI, C#

* Frontend: Vue.js/JS

* ML/AI: PyTorch, ONNX Runtime, Transformers, LangGraph, LangChain, Azure OpenAI, Azure AI Search, Vertex AI, Dialogflow CX, CoquiTTS, RAG/Graph-RAG, Guardrails, NLP pipelines

* LLM Integrations: OpenAI

* ETL: Apache NiFi

* DevOps/Cloud: GCP (Pub/Sub, FireStore GCP CloudRun etc), Azure (Container Jobs, Azure AI Search), Docker, GitLab CI/CD

* RDBMS: PostgreSQL/pgvector, SQL Server

  Résumé/CV: https://bit.ly/4h1uoWJ

  Email: whoshiring[dot]max[at]gmail[dot]com

I'm working on graph insight, a semantic graph tool for exploring research papers. It extracts keyphrases, builds a 3D graph, and lets you navigate from documents > topics > clusters.

So far: ~28k papers processed, 100k+ topics mapped. Use case: faster literature review, spotting hidden links, and seeing research areas as a connected landscape instead of isolated PDFs. I think this tool applicable for news/media streams too.

Example (Text-to-Speech papers): https://www.reddit.com/r/deeplearning/comments/1nic3ft/3d_se...

I’m curious - would this be useful as a standalone tool for researchers/engineers/other domain areas?

I like it. Looks really useful.

Thank you very much. In case you have ideas feel free to leave an issue on GitHub https://github.com/read-works/readworks

This is an amazing project. I like it.

TTS api for voice chatbots for customer support teams.