Staff ML Engineer (Europe/UK - Remote) in London

Sword Health is shifting healthcare from human-first to AI-first through its AI Care platform, making world-class healthcare available anytime, anywhere, while significantly reducing costs for payers, self-insured employers, national health systems, and other healthcare organizations. Sword began by reinventing pain care with AI at its core, and has since expanded into women's health, movement health, and more recently mental health. Since 2020, more than 700,000 members across three continents have completed 10 million AI sessions, helping Sword's 1,000+ enterprise clients avoid over $1 billion in unnecessary healthcare costs. Backed by 42 clinical studies and over 44 patents, Sword Health has raised more than $500 million from leading investors.

As a Staff AI Engineer on the Mind team, you will be the technical cornerstone of our end-to-end mental health platform. We view Mind as a highly sophisticated, multi-agent system that manages complete patient care pathways. In this staff-level role, you will architect the next generation of our agentic infrastructure. You will move beyond implementation to design the orchestration layers, memory systems, and RAG frameworks that allow multiple LLMs to work in concert. While you will work closely with our AI Research team on model training today, you will play a pivotal role in evolving our applied training capabilities and specialized fine-tuning for clinical environments.

What you’ll be doing:

• Agentic Architecture: Lead the design and scaling of complex multi-agent workflows, focusing on reliability, clinical safety, and sophisticated orchestration of multiple LLMs.
• Applied Model Evolution: Collaborate with AI Research to support and eventually spearhead post-training initiatives tailored for therapeutic domains.
• Technical Strategy: Define the long-term AI roadmap for the Mind team, balancing cutting-edge research with the pragmatic, high-availability needs of a production environment.
• Infrastructure Leadership: Oversee the development of robust evaluation frameworks and data pipelines that enable rapid iteration on both RAG performance and model behavior.
• Bridge Research & Production: Act as the primary technical liaison between AI Research and Engineering, ensuring state-of-the-art breakthroughs are successfully translated into scalable product features.

What you need to have:

• ML Expertise: 8+ years of professional experience in Machine Learning, with a proven track record of shipping complex AI products at scale.
• Agentic Orchestration: Significant experience building and maintaining production-grade Agentic AI systems involving multi-model coordination, complex memory management, and tool-use.
• Applied Training Knowledge: Practical experience with LLM fine-tuning and evaluation.
• Technical Stack: Expert-level Python and SQL; deep familiarity with modern AI orchestration frameworks and production software engineering best practices.
• High-Level Leadership: Experience setting technical direction, navigating deep ambiguity, and providing high-impact mentorship to senior engineers.
• Communication: Exceptional ability to translate technical complexity into strategic business value for both leadership and cross-functional stakeholders.

What we would love to see:

• Experience in MedTech or regulated environments where AI safety and interpretability are paramount.
• Expertise in cloud-native AI infrastructure.
• Active contributions to the LLM/Agentic AI open-source community.
• Previous AI research experience.

To ensure you feel good solving a big Human problem, we offer a stimulating, fast-paced environment with lots of room for creativity; a bright future at a promising high-tech startup company; career development and growth, with a competitive salary; the opportunity to work with a talented team and to add real value to an innovative solution with the potential to change the future of healthcare; a flexible environment where you can control your hours (remotely) with unlimited vacation; access to our health and well-being program; remote or hybrid work policy.