Senior ML Engineer

📋 Description

• Own ML projects end-to-end from exploration to production.
• Build agentic LLM systems with tools, retrieval and orchestration.
• Treat evaluation as core engineering work with eval sets and tests.
• Improve model quality via prompting, retrieval, distillation or fine-tuning.
• Work across the full AI stack: data prep, serving, monitoring.
• Partner with Product, Clinical, and Engineering; translate requirements.

🎯 Requirements

• Shipping ML systems to production that users depend on.
• Hands-on LLM work in production: prompting, tool calls, agent workflows.
• Rigorous evaluation: built eval datasets/frameworks.
• Strong ML fundamentals and clear tradeoff reasoning.
• Comfort with ambiguity turning problems into production.
• Solid engineering: production-grade code and distributed systems.

🎁 Benefits

• Exposure to healthcare AI and high-stakes domains.
• Open source contributions and knowledge sharing encouraged.
• Company-wide benefits aligned to local regulations.