AI Automation Engineer & Technical Producer for Oncology Podcast Factory
Budget: $2 – $8 USD
I am a physician looking to build a high-volume, automated oncology “audio network” similar to the Inception Point AI model. The goal is to position me and my hospital as global thought leaders by publishing hyper-specific, daily oncology micro-podcasts across major platforms (Spotify, Apple, YouTube, etc.).
I need an AI Automation Engineer & Technical Producer who can help design, build, and continuously improve an end-to-end “podcast factory” that:
Monitors oncology journals and sources (e.g., PubMed, ASCO, NEJM) via RSS/APIs or similar tools
Uses LLMs to summarize and script short, accurate, patient- and clinician-focused episodes
Integrates text-to-speech/voice cloning tools to generate high-quality audio
Automates publishing of 5–10 micro-shows per day across podcast platforms and potentially social/video platforms
Sets up basic analytics and reporting to track downloads, engagement, and content performance
Keeps the human review layer light (around 10–20% human touch) but high quality
You should be comfortable with:
AI tools (LLMs, prompt engineering, content pipelines)
Automation platforms (e.g., Make, Zapier, n8n, or custom scripts)
Podcast/audio workflows (production, hosting, distribution)
Basic data/reporting dashboards
Please share:
Relevant experience building content or podcast automation systems
Tools/stack you prefer and why
A brief outline of how you’d approach Phase 1 (MVP factory) and then scale it
Project is not related to blockchain or crypto in any way, so please only apply if your experience is in AI/content/podcasting rather than Web3.
I need an AI Automation Engineer & Technical Producer who can help design, build, and continuously improve an end-to-end “podcast factory” that:
Monitors oncology journals and sources (e.g., PubMed, ASCO, NEJM) via RSS/APIs or similar tools
Uses LLMs to summarize and script short, accurate, patient- and clinician-focused episodes
Integrates text-to-speech/voice cloning tools to generate high-quality audio
Automates publishing of 5–10 micro-shows per day across podcast platforms and potentially social/video platforms
Sets up basic analytics and reporting to track downloads, engagement, and content performance
Keeps the human review layer light (around 10–20% human touch) but high quality
You should be comfortable with:
AI tools (LLMs, prompt engineering, content pipelines)
Automation platforms (e.g., Make, Zapier, n8n, or custom scripts)
Podcast/audio workflows (production, hosting, distribution)
Basic data/reporting dashboards
Please share:
Relevant experience building content or podcast automation systems
Tools/stack you prefer and why
A brief outline of how you’d approach Phase 1 (MVP factory) and then scale it
Project is not related to blockchain or crypto in any way, so please only apply if your experience is in AI/content/podcasting rather than Web3.