AI / ML Engineer (m/w/d)
About the role
About Recare
As one of the leading German HealthTech companies, we are reshaping discharge management – technology-driven, patient-centered, and free from bureaucracy. In addition to our market-leading SaaS platform, we develop AI solutions that radically simplify processes in hospitals and for aftercare providers, relieve healthcare professionals, and refocus attention on patients. Today, we already connect two-thirds of all German hospitals with over 650 rehabilitation clinics and 25,000 nursing and homecare providers. With currently around 100 employees, we continue to grow – and we are looking for people with character who want to help us improve the healthcare system.
What to expect as our AI / ML Engineer (m/w/d)
- Purposeful work – your role will have a positive impact on patients, their families, and healthcare professionals.
- Company culture – we believe in flat hierarchies that promote high performance and strong team dynamics. We foster an environment characterized by mutual respect, loyalty, and recognition.
- Flexibility – we are a remote-friendly company offering flexible working hours. Workations are also possible by arrangement.
- Edenred card – which you can use according to your needs.
- Extra vacation day – so you can celebrate your birthday with your loved ones, you’ll have the day off.
In this role, you can make an impact and grow with us as AI / ML Engineer (m/w/d)
As a core member of the AI team, you will work on building cutting-edge agentic systems that work reliably in production environments where privacy and correctness are top priorities. You will have ownership of a small set of projects (ideally one) since we believe that minimizing context switches and enabling engineers to focus continuously is fundamental to building great applications.
- Agentic Applications: Build robust chat and other generative AI applications leveraging agentic frameworks. You will be responsible for designing and optimizing core agent behavior, including routing, tool calls/responses, context management, grounding, and instruction-following.
- Deployment and Integration: Develop and maintain infrastructure for deploying AI agents and generative AI applications for use in, e.g., REST APIs or web UIs, including containerization, orchestration, and API development.
- GenAI Observability: Set up and optimize generative AI observability pipelines, including logging, tracing, metrics, dashboards, and prompt management.
- Performance Evaluation: Quantify the real value of agentic systems based on observability data, custom evaluation metrics, and user feedback.
- Safeguarding Health Data: Embed security best practices and uphold compliance to protect sensitive health information.
- State-of-the-Art Technology & Implementation: Stay up to date with cutting-edge AI technologies, and translate them into technical reports, papers, and production-ready implementations.