Staff Research ML Engineer (Europe-based/Remote)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Staff Research ML Engineer (Europe-based/Remote) Europe 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. The Applied AI Team develops AI

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