Opportunity
We’re partnering with an ambitious, investor-backed health technology scale-up that is building a next-generation preventive healthcare platform powered by machine learning, multimodal data, and conversational AI.

This is a rare chance to join as one of the earliest technical hires and help shape both the product and the company. You’ll work directly with founders and senior technical leaders, taking ownership of problems that sit at the intersection of AI, healthcare, and product innovation.
If you enjoy building from first principles, shipping quickly, and seeing your work reach real users, this role offers an exceptional level of autonomy and influence.

About the Organisation
The business is developing technology that uses everyday consumer devices to make health screening and early risk detection dramatically more accessible. Their long-term vision is to create a trusted, intelligent health platform that combines digital signals, clinical data, and AI-driven decision support to help people identify potential issues earlier and engage with appropriate care pathways.

Backed by experienced investors and led by a team with deep expertise in machine learning, biostatistics, and healthcare technology, the company is now entering an exciting phase of product expansion and AI development.
The Impact You'll Have

As a Founding AI Engineer / Data Scientist, you won’t be maintaining existing models—you’ll be helping define what the AI stack becomes.

You will contribute to customer-facing capabilities such as:
  • Personalised recommendation systems
  • Multimodal biomarker estimation using video, audio, text, and behavioural signals
  • Predictive health modelling
  • AI-powered clinical reasoning and protocol generation
  • Foundational components for future conversational medical agents

You’ll also help establish the company’s ML infrastructure, deployment practices, and data foundations as the platform scales.

Key Responsibilities
  • Design, train, evaluate, and deploy machine learning models across multimodal datasets.
  • Build production-grade ML systems using Python and PyTorch.
  • Develop recommendation and decision-support capabilities that deliver measurable user value.
  • Work with large, heterogeneous datasets including audio, video, imaging, sensor, and clinical data.
  • Create robust data pipelines and contribute to the overall ML platform architecture.
  • Prototype and integrate modern AI techniques, including agentic and reasoning-based systems.
  • Collaborate closely with product, engineering, and domain experts to translate research into usable features.
  • Help define engineering standards, experimentation practices, and model monitoring processes.
  • Stay current with advances in applied AI, healthcare ML, and production ML tooling.

What We're Looking For
  • MSc or PhD in Machine Learning, Statistics, Computer Science, or a related quantitative discipline.
  • Strong industry experience in applied ML or data science (typically 4+ years, or 1+ year post-PhD).
  • Excellent Python development skills and strong software engineering fundamentals.
  • Hands-on experience with PyTorch or comparable deep learning frameworks.
  • Solid understanding of statistical modelling, machine learning, and experimental design.
  • Experience building or deploying ML systems in production.
  • Familiarity with recommendation systems, signal processing, or multimodal modelling.
  • Comfort working in a fast-moving, high-ownership environment.
  • Strong written and spoken English.

Desirable
  • Experience in healthcare, life sciences, or another regulated industry.
  • Published research or significant applied research experience.
  • Experience with LLM orchestration, AI agents, or reasoning architectures.
  • Knowledge of MLOps, model monitoring, and scalable deployment practices.
  • Exposure to clinical or biomedical datasets.

Why Join?
This is the kind of role where your decisions will matter immediately.
You’ll be joining a small, highly capable team that values initiative, curiosity, and practical problem-solving. The environment is designed for people who want to build rather than wait for permission.

In return, you’ll get:
  • Genuine ownership of critical AI and data initiatives.
  • Direct access to founders and strategic decision-making.
  • The opportunity to help shape an AI-first healthcare product from an early stage.
  • A mission with clear real-world impact.
  • Exposure to cutting-edge work across multimodal AI, digital health, and conversational systems.
  • A collaborative, low-ego culture focused on learning and execution.