Senior ML Engineer — Healthcare AI Care Platform

Sword Health, Inc.; Portugal; Hybrid; EUR 60,000 - 85,000; Full time

Job summary

Sword Health, Inc. is seeking a skilled ML engineer to own end-to-end ML projects, build agentic LLM systems, and drive rigorous evaluation in a production healthcare AI environment. You will work with Product, Clinical, and Engineering teams to translate clinical needs into technical decisions.

You will contribute across data prep, model adaptation, serving, monitoring, and feedback loops, mentoring peers while ensuring production reliability and safety in a fast-scaling healthcare setting.

Qualifications

• Experience shipping ML systems to production that users depend on.
• Hands-on LLM work in production: prompting, retrieval, tool calling, and agent-style workflows.
• Rigorous evaluation: built eval datasets and frameworks to prove improvements.
• Strong ML fundamentals and ability to reason about tradeoffs.
• Comfort with ambiguity and turning loosely defined problems into production-ready solutions.
• Solid engineering: production-quality code and distributed systems familiarity.
• Clear communication with technical and clinical stakeholders.

Responsibilities

• Own ML projects end-to-end from exploration to production deployment.
• Build agentic LLM systems with multi-step workflows and tool use.
• Treat evaluation as core engineering work with eval sets and regression tests.
• Improve model quality via prompting, retrieval, distillation or fine-tuning.
• Work across data prep, model adaptation, serving, and monitoring.
• Collaborate with Product, Clinical, and Engineering to surface tradeoffs early.
• Mentor engineers and share learnings to raise the team's capability.

Skills

Production ML

LLM adoption

Evaluation frameworks

ML fundamentals

Ambiguity tolerance

Distributed systems

Code quality

Cross-functional communication

Job description

Sword Health, Inc. is seeking a skilled ML engineer to own end-to-end ML projects, build agentic LLM systems, and drive rigorous evaluation in a production healthcare AI environment. You will work with Product, Clinical, and Engineering teams to translate clinical needs into technical decisions.

You will contribute across data prep, model adaptation, serving, monitoring, and feedback loops, mentoring peers while ensuring production reliability and safety in a fast-scaling healthcare setting.