Slingshot AI

Slingshot AI is the team behind Ash, the first AI designed for mental health. Our mission is to make support more accessible and help people change their lives in the ways they want.

We’re building a world-class team by empowering individuals with the autonomy, flexibility, and support they need to do their best work. We dream big, iterate fast, and care deeply. If that sounds like you, we’d love to hear from you.

Our team spans machine learning, product, engineering, conversational design, clinical, growth, and operations, with offices in both New York City and London.

We're a well-funded Series A company, having raised $93M from Andreessen Horowitz, Radical Ventures, Forerunner Ventures, plus top-tier tech investors involved in ElevenLabs, Captions, Shopify, Plaid, Notion, Canva, Twitch, Airtable, and many others.

The role

As Member of Technical Staff, you’ll join our tight-knit machine learning team working applied ML research, focused on model evaluations, data curation, and model training, working very closely with our product team. Our models have real-world impact, so this is a pragmatic, high-impact role. 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.

Some of our current work includes data collection, curation, continued pre-training, ablation studies, developing evals, supervising the creation of hand-crafted data, preference optimisation, training reward models, 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 with the latest open-source language models as well as frontier models through our deep partnerships with the largest AI labs. You’ll read papers and identify state-of-the-art techniques for us to learn from and contribute to our core ML research.

We write high-quality, typed, Zen code, mostly in Python. Our application backend is written in Kotlin and our ML stack utilises modern tooling in the ML space, including some that we’ve developed in-house (React/Typescript).

About you:

We expect our MTS to be highly autonomous and intelligent individuals who may not fit our exact mold. Feel free to apply even if you don't exactly have the right experience, if you’re ready to learn quickly on the job, or believe you can contribute in ways we haven’t thought about yet.

• Experience developing deep learning models in PyTorch, TensorFlow or JAX, include 3+ years in a production environment.

• Experience training open-source language models, especially for domain adaptation.

• Experience with basic software engineering, especially in a language other than Python. You should have an understanding of modern software architectures.

• Enjoy a fast-paced environment and make pragmatic decisions. Ultimately, you’d rather prove out an idea through quick MVP code, than present a slide deck to explain it.

• Excellent at explaining complex ideas to non-technical people.

• Understand and appreciate that deep learning is magic!

Key responsibilities:

• Conduct applied ML research to enhance our models' capabilities in the mental health domain, working closely with Product and Clinical teams to identify high-impact areas for improvement.

• Design and implement evals to measure model performance, establish benchmarks, and detect capability regressions before they reach production.

• Develop systems to help us scale model training and ensure model inference runs smoothly in production.

• Stay current with state-of-the-art ML research, identify promising techniques, and adapt them to our use case.

• Contribute to the full stack when needed, collaborating with other teams to integrate new models and ML capabilities into the Ash product, from prototype to production deployment.

What we offer:

• A chance to join a passionate tight-knit team working on something to change the world

• Competitive compensation (we target 90th percentile)

• Travel between our NYC / London offices

• Usual startup perks like free lunch in our offices + generous learning budget

• Generous budget to cover your personal therapy