Swordhealth5mo ago

Staff Research ML Engineer (Europe-based/Remote)

EuropeFull Timelead

Data ScienceOtherMachine Learning EngineerData

1 views0 saves0 applied

Apply Now

Quick Summary

Overview

Technical Tools

a11ydistributed-systemsmachine-learningmentoringtechnical-writing

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.

Own complex ML problems end-to-end - Take on the hardest technical challenges (like fine-tuning LLMs to maximize clinical outcomes) from initial exploration through production deployment and real-world iteration.

Drive technical strategy in your domain - Define how we approach model development, evaluation, and optimization for clinical AI applications.

Build and optimize production LLM systems - Design and implement fine-tuning pipelines, preference optimization (RLHF, DPO), and rigorous evaluation frameworks for clinical use cases.

Work deeply across the full AI stack - From data preparation and model training through deployment, monitoring, and iteration in production environments.

Influence across teams - Partner with Product, Clinical, and Engineering teams to shape technical decisions and ensure we’re solving the right problems.

Raise the technical bar - Mentor engineers, establish best practices, and help define what excellent ML engineering looks like at Sword.

May lead 1-2 engineers on specific projects, providing technical direction and mentorship.

Deep expertise in production ML systems - You’ve built and shipped ML systems that users depend on, with a track record of solving complex technical problems.

Production LLM experience - You’ve fine-tuned, evaluated, and deployed LLMs in production environments.

Experience with preference optimization - You’ve implemented techniques like RLHF, DPO, or similar approaches in production settings.

Strong ML fundamentals - You understand when to use different ML approaches, can design rigorous evaluation frameworks, and make principled technical tradeoffs.

End-to-end ownership - You’ve taken ambiguous, complex problems from initial exploration through production deployment and ongoing iteration.

Excellent engineering skills - You write production-quality code, understand distributed systems, and can debug complex ML pipelines.

Communication and influence - You can drive technical decisions across teams and explain complex tradeoffs to technical and clinical stakeholders.

Experience with healthcare AI or clinical applications and the unique challenges of building ML for high-stakes domains.

Track record of designing evaluation frameworks for LLMs in specialized domains.

Contributions to the ML community through open source, technical writing, or other knowledge sharing.

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);