Lead ML Engineer (Europe-based/Remote)

Sword Health

EuropehybridCompetitiveAdded 4 months agoPermanentRemote: Hybrid

English Required Applied ai Ai & algorithms

Sword Health

·Europe

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Lead ML Engineer (Europe-based/Remote)

Sword Health

Requirements

What you'll be doing:

Ship production ML systems that power clinical care - Write code daily, design architectures, and make technical decisions across our AI treatment management platform and Phoenix.
Lead a lean team of 2-4 ML engineers - Set technical direction, unblock your team, review code, and ensure you’re building the right things the right way.
Drive 0-1 ML initiatives - Identify high-leverage opportunities across the AI stack (prompt engineering, RAG, fine-tuning, agentic workflows), prototype fast, and push to production.
Raise the technical bar - Establish best practices for AI development, mentor engineers, and scale our ML engineering culture.
Partner with Product and Clinical teams - Shape what gets built and ensure our AI solutions actually improve patient outcomes.

What you need to have:

Proven ability to ship production ML systems - You’ve built and deployed models that real users depend on, and can show the impact.
Experience leading technical teams - You’ve led engineers before (whether as a tech lead, team lead, or manager), with an emphasis on pragmatic execution and delivery.
Hands-on experience with end-to-end ML pipelines - From data preparation through model deployment, monitoring, and iteration in production.
Strong engineering fundamentals - You write production-quality code in Python, work effectively with data (SQL), and can debug complex ML systems.
GenAI experience - You’ve worked with LLMs in production environments (RAG, tool use, orchestration, complex workflows, or fine-tuning).
Bias toward action - You ship iteratively, make decisions with incomplete information, and prioritize effectively to deliver value quickly.
Clear communication - You can explain technical tradeoffs to clinicians, product managers, and engineers.

Benefits

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 (digital therapist sessions);
Remote or Hybrid work policy;
To get to know more about our Tech Stack, check here.

Original Advert

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, including Khosla Ventures, General Catalyst, Transformation Capital, and Founders Fund. Learn more at www.swordhealth.com.

The Applied AI Team develops AI and ML solutions that power personalized clinical care at scale. Our work includes end-to-end AI treatment management systems that handle complete care pathways - from initial assessment through intervention selection and progress monitoring across various therapeutic domains. We are also building Phoenix, an AI Care Specialist that engages in ongoing dialogue with patients and provides clinical guidance throughout their recovery journey.

This work spans the full AI stack: prompt engineering, RAG implementations, model fine-tuning, and agentic workflows. We leverage both generative AI and classical machine learning depending on what the problem requires. All of our projects contribute to delivering digital care that reaches new levels of clinical quality and accessibility.

What we would love to see:

Experience with healthcare AI or clinical applications - you understand the unique challenges of building ML for high-stakes domains.
Track record of designing and running experiments to measure real-world impact (A/B tests, online evaluation, etc.).