Software Engineer - AI/Cloud

Key responsibilities

• Design, implement, and maintain backend services for data ingestion, processing and AI scoring. 
• Support development, validation, and deployment of AI models, including training pipelines, inference, and monitoring.  
• Collaborate with AI researchers and clinicians to translate clinical requirements into software features.  
• Participate in analyzing clinical performance data.  
• Produce the technical documentation we need for regulatory compliance 
• Follow software engineering best practices: code reviews, tests, and reproducible workflows.

Required qualifications

• M.Sc. in Engineering, Computer Science, Data Science or related fields or equivalent professional experience.
• Practical programming experience 
• Experience with data analysis, statistics, signal processing, AI/ML or related areas.  
• Strong written and verbal English communication skills.  
• Curiosity and willingness to learn across software, ML and clinical domains.

Nice to have

• Experience with cloud development (AWS, serverless, containers).  
• Experience with ML frameworks (TensorFlow, PyTorch) and MLops practices. 
• Knowledge of scientific best practices and experience contributing to papers.

Technical stack

• Our tech stack includes Python, AWS serverless, and Tensorflow. 
• Our development tools include Atlassian tools (Bitbucket, Jira, Confluence, etc.), Pantsbuild and more.
• Our data is mostly time series of physiological signals (EEG, ECG, SpO2, breathing, etc), with some structured data elements, and text.
• You’re not expected to know everything — we value willingness to learn.

The job application, CV, and cover letter may be submitted in English or Icelandic.

The right person for this role thrives in a supportive and highly collaborative environment, where giving and receiving direct and constructive feedback is an integral part of our growth and success. We seek individuals who are self-motivated, eager to continuously learn, and committed to applying new knowledge to their work. This is especially important in our regulated environment, as we operate at the cutting edge where technology, medicine, and science intersect.