Senior ML Engineer

Sword Health; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Sword Health is hiring for a research-driven ML Engineer to own end-to-end AI projects in production, from exploration to deployment and iterations with real users.

You will build agentic LLM systems, design multi-step workflows, and partner with Product, Clinical, and Engineering to translate clinical requirements into technical decisions while advancing evaluation, safety, and reliability at scale.

Qualifications

• Experience shipping ML systems to production that people actually depend on.
• Hands-on LLM work in production: prompting, retrieval, tool calling, and agent-style workflows.
• A rigorous approach to evaluation: built eval datasets and frameworks and can distinguish signal from noise.
• Strong ML fundamentals: reason about tradeoffs and pick suitable approaches.
• Comfort with ambiguity: turn loosely defined problems into production-ready solutions.
• Solid engineering skills: production-quality code, distributed systems, and debugging ML pipelines.
• Open source contributions or technical writing demonstrate knowledge sharing.

Responsibilities

• Own ML projects end-to-end from exploration to production deployment.
• Build agentic LLM systems with multi-step workflows and tool use.
• Design eval sets, offline/online harnesses, LLM-as-judge pipelines.
• Improve model quality with prompting, retrieval, distillation, or fine-tuning.
• Work across data prep, model adaptation, serving, and monitoring.
• Partner with Product, Clinical, and Engineering to translate requirements into technical decisions.
• Mentor engineers and share learnings across the team.

Skills

End-to-end ML in prod

LLM workflows

Evaluation frameworks

Strong ML fundamentals

Clear communication

Open source contributions

Job description

At Sword, we’re building AI to heal billions and unlock humanity’s full potential. In doing so, we’re pioneering AI Care, a fundamentally new approach to healthcare built for medical reasoning, safety, and real-time treatment, not generic technology applied after the fact. As both a clinical-centric frontier AI lab and an applied AI platform, Sword is reimagining how care is delivered at scale, removing traditional barriers like appointments, waiting rooms, and stigma so more people can access the care they need—and ultimately get back to lives lived in full.

Since 2020, Sword has expanded across physical therapy, women’s health, cardiometabolic, and mental health, and is now moving beyond the session to a fully AI-native, 24/7 care program that brings physical activity, therapeutic exercise, psychotherapy, nutrition, and behavior change into one connected experience. More than 700,000 members across three continents have completed over 10 million AI sessions, helping 1,000+ enterprise clients avoid more than $1 billion in unnecessary healthcare costs. Backed by 42 clinical studies, 44+ patents, and more than $500 million raised from leading investors including Khosla Ventures, General Catalyst, and Founders Fund, Sword is defining a new standard for healthcare.

AIProficiency at Sword

AI fluency is a core expectation at Sword. Every candidate is assessed against our three-level framework — be ready to share real examples of how AI is already part of how you work.

Explorer (Level 1) — Uses AI daily to boost personal productivity

Builder (Level 2) — Creates workflows and tools that elevate the whole team

Integrator (Level 3) — Embeds AI into products and processes at scale

Every hire must demonstrate at least Level 1. The expected level will vary depending on the seniority of the role.

What you’ll be doing

• Own ML projects end-to-end: take problems from exploration through production deployment and keep iterating once real users are on them;
• Build agentic LLM systems: design multi‑step workflows with tool use, retrieval, and orchestration, and make them reliable enough for clinical settings;
• Treat evaluation as core engineering work: build eval sets, offline and online harnesses, LLM‑as‑judge pipelines with human review, and regression tests that catch quality drops before they reach users;
• Improve model quality with whatever fits the problem: prompting, retrieval, distillation, or fine‑tuning, chosen on evidence rather than habit;
• Work across the full AI stack: data prep, model adaptation, serving, monitoring, and the feedback loops that keep systems improving in production;
• Partner with Product, Clinical, and Engineering: translate clinical requirements into technical decisions and surface trade‑offs early;
• Help the team get better: review code, share what you learn, and mentor engineers earlier in their careers.

What you need to have

• Experience shipping ML systems to production that people actually depend on;
• Hands‑on LLM work in production: prompting, retrieval, tool calling, and agent‑style workflows;
• A rigorous approach to evaluation: you've built eval datasets and frameworks, and you can tell a real improvement from noise;
• Strong ML fundamentals: you know which approach fits which problem and can reason clearly about tradeoffs;
• Comfort with ambiguity: you've taken loosely defined problems and turned them into something running in production;
• Solid engineering skills: production‑quality code, familiarity with distributed systems, and the patience to debug messy ML pipelines;
• Clear communication with both technical and clinical stakeholders;
• Experience with fine‑tuning or preference optimization (RLHF, DPO, or similar);
• Healthcare AI, or other high‑stakes domains where errors carry real cost;
• Built agent frameworks or evaluation tooling from scratch;
• Open source contributions, technical writing, or other knowledge sharing.

*The range below reflects base, variable, and equity for this role.

This is a starting point, not a ceiling — once someone joins and proves they're outlier talent, we adjust quickly to make sure their compensation matches their impact.

Job titles may span more than one career level, so actual pay depends on skills, qualifications, experience, location, and market demand, among other factors. The range reflects base salary plus any variable, bonus, or sales incentives, and our estimate of the value of private company stock options where applicable. It's subject to change, and future stock value isn't guaranteed. Sword also offers additional benefits beyond total compensation.

Total Compensation Range

Country-specific benefits may vary and will be detailed separately.

Sword Health complies with applicable Federal and State civil rights laws and does not discriminate on the basis of Age, Ancestry, Color, Citizenship, Gender, Gender expression, Gender identity, Gender information, Marital status, Medical condition, National origin, Physical or mental disability, Pregnancy, Race, Religion, Caste, Sexual orientation, and Veteran status.

Voluntary Self‑Identification

For government reporting purposes, we ask candidates to respond to the below self‑identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Sword’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A \"disabled veteran\" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.

A \"recently separated veteran\" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An \"active duty wartime or campaign badge veteran\" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An \"Armed forces service medal veteran\" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.

At Sword, we use AI to surface the right information at the right moment. However, AI never replaces human judgment.