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Slingshot AI

The Foundation Model for Human Psychology

Actively Hiring Growing Fast Top Tier Investor

Overview

Employees
11-50
Locations
New York City, London
We're a team of machine learning and product engineers training task-specific generative models for psychology. Our mission is to use AI to make mental healthcare more accessible and to help people change their lives in the ways they want. We partner with organizations around the globe and power use cases, including AI-assisted crisis text response and AI counseling, while securing best-in-class datasets to power our models.

Success to us means every human being in need of support having somewhere to go. We're a well-funded, seed-stage startup backed by top-tier tech investors involved in ElevenLabs, Captions, Shopify, Plaid, Notion, Canva, Twitch, Airtable, and others.

We're building a powerful team by empowering our engineers with the autonomy, flexibility, and resources to do their best work. We dream big and iterate fast. If that sounds like home, we'd love to hear from you.

The Team

Daniel started coding at age 8 and started training models in high school. At 16, he dropped out of high school and moved to London to pursue his study and research. He graduated university top of his class at 19 and was awarded ‘distinguished’ by Imperial for his post-grad research in AI for mental health. As an ML Engineer, he led Instabase’s pivot into GenAI. He raised $6M pre-team at age 22 to develop the tools for training task-specific generative models that now power our machine learning research.

Neil dropped out of medical school to co-found Casper, the sleep company, which he helped grow to $500M+ in revenue and IPO’d in 2020. Improving wellbeing through sleep led him to mental health, where he joined the board of [PsychHub](https://psychhub.com/). He’s invested in 200+ companies like Ro, Affirm, Relativity, Archer, Figure, and Together.AI.

Our team has expertise in model training, product engineering, and psychology. Our engineers includes team leaders who have joined us as individual contributors, two former CTOs, and collective experience from across Big Tech.

Industries

Machine Learning Artificial Intelligence / Machine Learning

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