Senior Machine Learning Engineer (LLMs/Clinical NLP)

TL;DR

Senior Machine Learning Engineer (LLMs/Clinical NLP): Building and productizing large language model capabilities for clinical summarization and medical text generation with an accent on clinical risk and model reliability. Focus on training, fine-tuning, and optimizing LLM inference services to improve healthcare outcomes through advanced AI infrastructure.

Location: Hybrid role based in Copenhagen, Denmark

Company

hirify.global is an AI platform building the intelligence layer for global healthcare, designed to assist clinicians and improve patient outcomes through medical-grade speech recognition and reasoning.

What you will do

• Build and refine clinical NLP systems for summarization and structured data extraction.
• Train and fine-tune transformer-based models using modern post-training frameworks.
• Design evaluation strategies for generative systems, including human review and quality gates.
• Operate and scale LLM inference services using vLLM to ensure low latency and high reliability.
• Optimize production models through quantization, caching, and efficient decoding strategies.
• Collaborate with cross-functional teams to integrate NLP components into end-to-end production pipelines.

Requirements

• Must be based in or able to work from the Copenhagen office.
• Strong proficiency in Python and experience contributing to production-grade codebases.
• Hands-on experience with LLMs for NLP, including training or fine-tuning transformer models.
• Proven ability to deploy and operate ML systems beyond notebooks, including CI/CD and monitoring.
• Experience designing robust evaluation methods for generative AI systems.
• Master’s degree in a quantitative field or equivalent professional experience.

Nice to have

• Experience with healthcare data and clinical NLP standards.
• Deep understanding of privacy and safety requirements in clinical environments.
• Experience collaborating with clinical domain experts.

Culture & Benefits

• Collaborative research and engineering environment.
• Hybrid working model with office presence in Copenhagen.
• Access to modern MLOps tooling and infrastructure.
• Opportunity to influence the future of medical AI.
• Professional growth opportunities within a specialized R&D group.