AI Research Scientist / Engineer (Generative World Models)

Location: Copenhagen, Denmark; onsite work required. Candidates must be based in Copenhagen, Denmark, or willing to relocate.

Company

hirify.global is building a real-time multimodal AI data layer for point-of-care healthcare, generating digital twins of patients and care environments through computer vision and behavioral data.

What you will do

• Own research and development for Cassandra, hirify.global’s generative world model for healthcare.
• Improve the end-to-end pre-training pipeline, including behavioral data representation, tokenization, model architecture, training objectives, and scaling.
• Design experiments and develop approaches for continuous-time event modeling, irregularly sampled data, and long-term dependencies.
• Develop and productionize downstream applications based on Cassandra’s learned representations.
• Improve prediction of resident fall risk within the next five minutes and explore forecasting behavior changes and simulating care interventions.

Requirements

• Hands-on experience training large-scale sequence models such as Transformers, state-space models, or LLMs.
• Deep understanding of neural network architectures, optimization, training dynamics, and scaling laws.
• Strong Python and PyTorch skills, including experience building efficient, reliable training and evaluation pipelines.
• Ability to independently design experiments, interpret results, and translate research ideas into working implementations.
• Solid mathematical foundations in machine learning, probability, and statistics.
• Research-driven, hands-on approach with the ability to read papers, challenge assumptions, and implement ideas.
• Strong technical intuition, ownership, autonomy, and ability to take ideas from hypothesis to production.

Nice to have

• Research or engineering experience with LLM pre-training, including architecture design, data mixtures, training objectives, or scaling experiments.
• Experience with generative modeling of sequential, temporal, or event-based data.
• Familiarity with continuous-time models, point processes, time-to-event prediction, or survival modeling.
• Experience with long-context architectures such as Mamba, recurrent models, or efficient attention mechanisms.
• Experience with distributed training, GPU optimization, and performance profiling.
• Impactful ML research demonstrated through publications, open-source contributions, or production systems.

Culture & Benefits

• Competitive salary and participation in the warrant program.
• Work with state-of-the-art technology in a pioneering healthcare AI field.
• Access to a large in-house training cluster.
• In-office workplace with a learning-focused environment.
• Hands-on culture emphasizing ownership, entrepreneurship, continuous learning, and real-world impact.