FT3
Company Description
FT3 Media
is an emerging media company building a new model for journalism: pre-narrative, fact-first reporting. In an era of collapsing public trust, FT3 is developing proprietary bias-detection technology to deliver raw, verifiable facts before interpretation, framing, or spin. By exposing how narratives are constructed rather than assigning ideological labels, FT3 aims to give audiences the tools to think critically and independently. As an up-and-coming platform, FT3 Media seeks to redefine how news is created and consumed—laying the groundwork for a more transparent, trustworthy, and intellectually empowering media future.
Full-Stack Engineer (Bias Detection & Media Transparency)
We’re looking for a full-stack engineer to build bias detection technology that analyzes news articles at the sentence level. You’ll own the pipeline end-to-end — from article ingestion through bias scoring to user-facing visualizations.
You’ll design systems that can process thousands of articles daily, identifying patterns like
loaded language, source imbalance, and narrative framing . That means:
Building ingestion pipelines (RSS, APIs, scrapers) and real-time processing (Kafka, AWS Lambda, or similar).
Integrating multiple APIs (NewsGuard, AWS Comprehend, OpenAI) and stitching them into a scalable scoring engine.
Developing classification and clustering models (text classification, embeddings, FAISS).
Creating interactive interfaces — bias heatmaps, overlays, and clustering views — in React/D3.js that make bias transparent to users.
Adding monitoring, retries, and audit logs so the system is reliable at scale.
Designing simple human-in-the-loop tools (Labelbox, Prodigy, Retool dashboards) for annotation and QA.
What you bring
Strong with
Python
(data pipelines, NLP, backend services)
Solid with
JavaScript/React
(building clear, intuitive UIs)
Hands-on with
NLP/NLU
(classification, sentiment, embeddings)
Comfortable integrating and orchestrating
multiple APIs and services
Cloud deployment experience (AWS or GCP)
Pragmatism: you know when to fine-tune a model, when to call an API, and when to keep it simple
This is a
0→1 role in an early-stage environment . You’ll shape the foundation of our bias detection platform. Clarity, speed, and reliability matter more than perfection.
#J-18808-Ljbffr
is an emerging media company building a new model for journalism: pre-narrative, fact-first reporting. In an era of collapsing public trust, FT3 is developing proprietary bias-detection technology to deliver raw, verifiable facts before interpretation, framing, or spin. By exposing how narratives are constructed rather than assigning ideological labels, FT3 aims to give audiences the tools to think critically and independently. As an up-and-coming platform, FT3 Media seeks to redefine how news is created and consumed—laying the groundwork for a more transparent, trustworthy, and intellectually empowering media future.
Full-Stack Engineer (Bias Detection & Media Transparency)
We’re looking for a full-stack engineer to build bias detection technology that analyzes news articles at the sentence level. You’ll own the pipeline end-to-end — from article ingestion through bias scoring to user-facing visualizations.
You’ll design systems that can process thousands of articles daily, identifying patterns like
loaded language, source imbalance, and narrative framing . That means:
Building ingestion pipelines (RSS, APIs, scrapers) and real-time processing (Kafka, AWS Lambda, or similar).
Integrating multiple APIs (NewsGuard, AWS Comprehend, OpenAI) and stitching them into a scalable scoring engine.
Developing classification and clustering models (text classification, embeddings, FAISS).
Creating interactive interfaces — bias heatmaps, overlays, and clustering views — in React/D3.js that make bias transparent to users.
Adding monitoring, retries, and audit logs so the system is reliable at scale.
Designing simple human-in-the-loop tools (Labelbox, Prodigy, Retool dashboards) for annotation and QA.
What you bring
Strong with
Python
(data pipelines, NLP, backend services)
Solid with
JavaScript/React
(building clear, intuitive UIs)
Hands-on with
NLP/NLU
(classification, sentiment, embeddings)
Comfortable integrating and orchestrating
multiple APIs and services
Cloud deployment experience (AWS or GCP)
Pragmatism: you know when to fine-tune a model, when to call an API, and when to keep it simple
This is a
0→1 role in an early-stage environment . You’ll shape the foundation of our bias detection platform. Clarity, speed, and reliability matter more than perfection.
#J-18808-Ljbffr