Member of Technical Staff
Member of Technical Staff

Member of Technical Staff

Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
Slingshot AI

At a Glance

  • Tasks: Join our machine learning team to enhance AI for mental health and improve user experience.
  • Company: Slingshot AI, creators of Ash, the first AI designed for mental health support.
  • Benefits: Competitive pay, travel between NYC and London, free lunch, and a generous learning budget.
  • Other info: Join a passionate team dedicated to changing lives through accessible mental health support.
  • Why this job: Make a real-world impact while working with cutting-edge AI technology in a supportive environment.
  • Qualifications: Experience in deep learning models and software engineering; eager to learn and innovate.

The predicted salary is between 36000 - 60000 ÂŁ per year.

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 are a well‑funded Series A company, having raised $93 million from top‑tier tech investors.

The role involves joining our tight‑knit machine learning team working on applied ML research, focused on model evaluations, data curation, and model training, working closely with our product team. Our models have real‑world impact, making this a pragmatic, high‑impact role. 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 and curation
  • Continued pre‑training
  • Ablation studies
  • Developing evals
  • Supervising the creation of hand‑crafted data
  • Preference optimisation
  • Training reward models
  • State‑of‑the‑art reinforcement learning research

You will 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.

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 required:

  • Developing deep learning models in PyTorch, TensorFlow or JAX, including 3+ years in a production environment.
  • Training open‑source language models, especially for domain adaptation.
  • Basic software engineering, especially in a language other than Python.
  • An understanding of modern software architectures.
  • Enjoying a fast‑paced environment and making pragmatic decisions.
  • Excellent at explaining complex ideas to non‑technical people.

Key responsibilities include:

  • Conducting applied ML research to enhance our models’ capabilities in the mental health domain.
  • Designing and implementing evals to measure model performance, establish benchmarks, and detect capability regressions before they reach production.
  • Developing systems to help us scale model training and ensure model inference runs smoothly in production.
  • Staying current with state‑of‑the‑art ML research, identifying promising techniques, and adapting them to our use case.
  • Contributing to the full stack when needed, collaborating with other teams to integrate new models and ML capabilities into the Ash product.

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.

Member of Technical Staff employer: Slingshot AI

Slingshot AI is an exceptional employer, offering a unique opportunity to work at the forefront of mental health technology in London. With a strong emphasis on autonomy and flexibility, employees are empowered to innovate and make a real-world impact through their contributions. The company fosters a collaborative and supportive work culture, providing competitive compensation, generous learning budgets, and even personal therapy coverage, making it an ideal place for those seeking meaningful and rewarding employment.
Slingshot AI

Contact Detail:

Slingshot AI Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Member of Technical Staff

✨Tip Number 1

Network like a pro! Reach out to people in the industry, especially those at Slingshot AI. A friendly chat can open doors that applications alone can't.

✨Tip Number 2

Show off your skills! If you’ve got a portfolio or GitHub with projects related to machine learning or coding, make sure to highlight them during interviews. It’s all about proving you can walk the walk!

✨Tip Number 3

Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and be ready to discuss your past projects in detail. We want to see your thought process!

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.

We think you need these skills to ace Member of Technical Staff

Machine Learning
Model Evaluation
Data Curation
Model Training
Python
PyTorch
TensorFlow
JAX
Software Engineering
Modern Software Architectures
Deep Learning
Communication Skills
Fast-Paced Environment Adaptability
MVP Development

Some tips for your application 🫡

Show Your Passion: When writing your application, let your enthusiasm for mental health and AI shine through. We want to see how you connect with our mission and how you can contribute to making support more accessible.

Tailor Your Experience: Make sure to highlight your relevant experience in machine learning and software engineering. We’re looking for specific examples of your work with deep learning models and any projects that demonstrate your ability to iterate quickly and effectively.

Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on communicating your ideas in a way that’s easy to understand, especially for non-technical folks.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!

How to prepare for a job interview at Slingshot AI

✨Know Your ML Stuff

Make sure you brush up on your machine learning knowledge, especially around model evaluations and training. Be ready to discuss your experience with frameworks like PyTorch or TensorFlow, and have examples of how you've applied them in real-world scenarios.

✨Show Your Pragmatic Side

This role is all about making quick, impactful decisions. Prepare to share instances where you've developed MVPs or made fast-paced decisions that led to significant outcomes. Highlight your ability to iterate quickly and adapt to new challenges.

✨Communicate Clearly

You’ll need to explain complex ideas to non-technical folks, so practice simplifying your explanations. Think of ways to convey your technical knowledge in a relatable manner, perhaps by using analogies or straightforward language.

✨Stay Current with Trends

Familiarise yourself with the latest trends in ML research and be prepared to discuss how they could apply to the mental health domain. Bring along any interesting papers or techniques you've come across that could benefit the team, showing your proactive approach to learning.

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