Senior ML Engineer

📋 Description

• Own ML projects end-to-end from exploration to production deployment and monitoring.
• Design agentic LLM systems with tool use, retrieval, and orchestration for healthcare environments.
• Develop robust evaluation strategies, including datasets, offline/online testing, and AI-assisted
• Improve model performance via prompt engineering, retrieval optimization, or fine-tuning.
• Work across ML lifecycle: data prep, model adaptation, serving, monitoring, and feedback loops.
• Collaborate with Product, Clinical, and Engineering to translate requirements into solutions and

🎯 Requirements

• Proven experience shipping production ML systems used by real users/customers.
• Hands-on deployment of LLM-based systems: prompting, retrieval, tool calling, agent-style workflows.
• Strong evaluation expertise and ability to distinguish meaningful improvements from noise.
• Strong foundations in ML and selecting appropriate approaches based on evidence and trade-offs.
• Experience turning ambiguous problems into reliable production solutions.
• Strong software engineering, distributed systems, and debugging ML pipelines; clear communication

🎁 Benefits

• Competitive compensation adjusted to local market and cost of living in Europe.
• Total compensation may include base salary, variable pay, bonuses or incentives, and equity where
• Compensation reviewed based on skills, location, and impact; opportunity for growth as
• Country-specific benefits aligned with local regulations and market practices.
• Opportunity to work on high-impact AI systems in healthcare.