We're a team of machine learning engineers training task-specific generative models for psychology. Our goal is to build an AI therapist to help people change their mind and their lives in the ways that they want to. We partner with organizations around the globe and power use cases, including AI-assisted crisis text response, while securing best-in-class datasets to power our models.
We're a well-funded, seed-stage startup backed by top-tier tech investors involved in Huggingface, ElevenLabs, Replit, 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. As Member of Technical Staff, you’ll work with our founding team across ML research and product development. To be successful in this role, you have to care about how these models perform to help people in the real world - more than how they perform on artificial evals. We ship a lot. You’ll be able to work at a faster pace than almost anywhere else while writing high-quality code and producing meaningful scientific insights.
You may work on data collection, curation, continued pre-training, ablation studies, evals, supervising the creation of hand-crafted data, preference optimization, and state-of-the-art reinforcement learning research. You'll also contribute to our end-user product, improving user experience through your work on our models and model orchestration.
You’ll be working on the latest language models, ranging from open-source 70B & 405B to frontier models through our deep partnerships with the largest AI labs. and contribute to our core ML research: aligning language models towards successful long-term trajectories.
Our application backend is written in Kotlin and our ML stack (PyTorch) utilizes modern tooling in the ML space, including some that we’ve developed in-house in Typescript. We write high-quality, typed, code.
Experience fine-tuning language models, like Llama.
~ Experience with software engineering on a product, e.g. React, Swift, Kotlin, Java, etc., including a strong understanding of modern software architectures.
~ Competitive compensation (90th percentile)
Hybrid environment, highly collaborative, fast-paced culture