Senior Machine Learning Engineer

at  Ground News

WHO WE ARE?

Ground News is a platform that makes it easy to compare news sources, read between the lines of media bias and break free from algorithms.
In a world where political polarization and media distrust are at an all-time high, Ground News offers people a better way to stay informed and open-minded. Our mobile app, web app, and browser extension are home to a community of mindful newsreaders who use our news comparison platform to easily see every side of a story and engage with news beyond their filter bubble.

Unlike most news companies, our audience and our values do not align with any specific political ideology. Unlike most tech platforms, we don’t use manipulative algorithms to keep users on our platform to sell more ads. We are supported by our readers who pay for a subscription to build a more nuanced understanding of the news, the world, and themselves.

• #1 on Product Hunt (Oct 19, ‘20), #2 (Nov 17, ‘21), #2 (Mar 26, ‘21)
• Techstars portfolio company
• Winner of Digital News Innovation Challenge by Facebook
• Winner of Mobile Apps Showdown at CES
• Featured at Mobile World Congress
• Featured on New York Times, Financial Times, Newsmax, Forbes and more
• Our site has even been retweeted by the POTUS

THE OPPORTUNITY - SENIOR MACHINE LEARNING ENGINEER

We’re looking for someone who can get excited about building tools to help people navigate and understand the vast news/information ecosystem we live in. As part of the team, you will be at the forefront of pioneering new AI applications, tailored for the news landscape. You will be pushing the limit on what Large Language Models can do, with access to rich data sets consisting of 60,000+ articles ingested per day from over 50,000 news sources.

• Design and implement advanced prompt engineering techniques to coax the best outputs from different LLMs. This will involve experimenting with and benchmarking various generative models
• Design and maintain a scalable infrastructure for new AI-powered features and products while working closely with Full-Stack and DevOps engineers
• Design and build out a series of internal ML products, including spam detectors, clustering algorithms, and recommendation engines.
• Apply non-LLM ML frameworks (i.e. vector search, knowledge graphs) to existing products
• Build data pipelines for a very large news-specific dataset expanding in real time
• Prepare and use data for various applications including ML, client use and analytics