Help us build the future of mental health by developing our new AI Therapist for end-to-end care in the US.
About Limbic
Limbic’s vision is to ensure the highest quality therapy is accessible to everyone, everywhere.
Limbic is already used in over 50% of Talking Therapies in the NHS, which makes us the largest-ever deployment of generative AI for direct patient care. Using Limbic Access we augment clinical care and reduce barriers to accessing therapy at scale - deployed with safety as the top priority and the only AI mental health chatbot with UKCA Class IIa certification.
Limbic is live in the US, interacting with thousands of patients there every week. Furthermore, we are launching an AI therapist doing end-to-end care in the US, and we are looking for a mission-driven engineer to help us build this critical new product.
The Role
As an AI/ML Engineer, you will sit at the intersection of computational psychiatry, clinical science, and software engineering. You will drive the development of AI interventions that engage users, predict recovery milestones, and orchestrate evidence-based therapeutic sessions. This role is specifically focused on building and refining our end-to-end care AI therapist for the US market.
What You’ll Do
Drive effective session orchestration and lead the implementation of our Evidence-Based Intervention Library.
Develop AI features tailored for product retention and engagement.
Implement features involving expectation setting, gamification, and reinforcement learning for the personalization of care.
Optimize our recovery data collection processes, focusing on the methods, timing, and predictive modelling of PHQ-9s.
Provide occasional analysis and modelling support for additional clinical research projects.
What You’ll Bring
You must meet one of the following educational and experience backgrounds:
A PhD in Computational Psychiatry or a related field, coupled with demonstrated industry experience in Data Science, Product, or ML engineering.
OR A BSc/MSc in a Computational Psychiatry related field (research focus) plus 2 years of experience in ML engineering or Data Science within an Engineering/Product Development environment.
Proficiency in either Python or Typescript/Javascript.
An expert approach to hypothesis-driven work, with a track record of balancing product development with scientific rigour.
Experience in Eval-driven-development.
Experience using Machine Learning in a production environment or via high-impact scientific publications (e.g., predictive modelling, reinforcement learning).
Experience modelling text/language data, including building LLM classifiers and using vector-based methods.
Experience modelling longitudinal data and working with databases (SQL or NoSQL).
A strong understanding of evidence-based mental health care (such as Cognitive Behavioural Therapy) and a deep interest in the causal mechanisms that drive therapeutic benefit.
Proficiency with version control systems, preferably Git.
Ideal but not required: Experience building an LLM agent harness.
The ability to work from our London (Spitalfields) office on Tuesdays and Thursdays, with the flexibility to work remotely or from the office on other days of the week.
Please note: Limbic cannot provide visa sponsorship.
Benefits & Wellbeing
Competitive salary and equity share options.
An amazing office in central London (Spitalfields) for our collaborative team days on Tuesdays and Thursdays, paired with a flexible/hybrid working model on Mondays, Wednesdays, and Fridays.
25 days PTO plus bank holidays.
Company pension scheme (UK).
Enhanced parental leave packages (UK).
Support with purchasing work-related books and materials.
Quarterly Life Days: Enjoy 4 paid days off per year (one each quarter) to use whenever you choose to relax, recharge, or take care of personal matters.
Mental Health Support: Access to dedicated mental health support services.
We encourage women and individuals from diverse backgrounds to apply and join our team. We believe in creating an inclusive and supportive work environment where everyone can contribute their best.