Head of Research

About the role

Many large companies make billions each year by monetizing Americans’ personal data. At Neon, we’re finally cutting consumers in on the deal. Neon allows our users to make hundreds (or even thousands) of dollars per year by securely selling their anonymized data. We recently raised $25 million dollars from Lightspeed, Upper
90, Upfront Ventures, and other cool investors.

Your mission will be to transform Neon’s unique consumer data streams into the gold standard for AI training and evaluation. As the Head of Research
, you will bridge the gap between our 500,000+ mobile users and the world’s leading AI labs, by directly interfacing and collaborating with your peers in these labs. You will define our research agenda, establishing Neon as a premier authority in audio data research and evaluation science.

• Authorization to work in the US.
• Track record of impactful
  AI/ML research
  , specifically focused on data evaluation, oversight, and generative AI.
• Significant audio and multimodal expertise, able to understand and clearly articulate the latest developments in the space. Speech specific expertise preferred.
• Deep engagement with the AI research community
  ; you speak the language of frontier labs and understand the current trends in model training and evaluation.
• A "Founder’s Mentality"—you are comfortable with ambiguity and have a proven ability to translate complex research insights into production-ready data products.
• Exceptional communication skills
  , capable of building relationships with top-tier researchers while clearly articulating Neon’s value proposition to partners.
• Experience with Python and Py Torch , designing and conducting rigorous ML experiments and evaluations.

• Published authorship in top-tier AI/ML venues such as NeurIPS, ICML, ICLR, or CVPR.
• Strong record of publications in data evaluations, especially for audio/speech, or multimodal.
• Experience building technical communities or academic advisory boards from the ground up.
• Specific expertise in evaluation science
  , including AI-assisted evaluation (RLAIF) or designing benchmarks for frontier capabilities.
• An active presence on X or other research channels
  , demonstrating thought leadership in the AI data conversation.