Senior ML Engineer
New
S
SwordHealthcare AI
This position is open to candidates based anywhere in Europe.Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- Machine LearningPrompt EngineeringDistributed Systems
Requirements
- 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.
Responsibilities
- 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 tradeoffs early.
- Help the team get better: review code, share what you learn, and mentor engineers earlier in their careers.
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