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Senior AI Researcher – Health AI & Multimodal Models

Neko Health AB

Stockholms län, Danderyd

Previous experience is desired

9 days left
to apply for the job

Role Purpose:

Neko is building toward a multimodal model that predicts disease and health trajectories beyond what human doctors can do today, grounded in proprietary sensor and medical label data no one else has. This role sits inside the Innovation group and turns that ambition into a concrete data and metrics foundation: deciding where Neko's labelling effort goes next, and defining the org-level metrics that connect real medical outcomes to AI progress, a genuinely frontier problem, not an incremental one.

What You'll Deliver in the First 6 - 12 months:

  • Set the research agenda for Neko's AI across its three horizons: narrow diagnostic models, context synthesis, and the eventual multimodal health model.
  • Determine where Neko builds proprietary models and where it uses and adapts frontier models from external labs.
  • Stay at the frontier of health AI research and bring that knowledge into the organisation continuously.
  • Work closely with the CEO, Medical Innovation and Data Science teams to ensure the research roadmap connects to what ships.
  • Represent Neko in the scientific community, through publications, conference presence, and relationships with leading research groups.
  • Act as a talent magnet: the presence that makes world-class researchers want to join Neko.
  • Build and maintain relationships with the best AI and health AI researchers globally, in academia and industry.
  • Create an environment where rigorous science and production deployment coexist.
  • Partner with the hardware and programme management teams to ensure the right data is being captured, labelled, and structured from the point of collection.
  • Help the organisation understand how to work with proprietary sensor data, medical labels at scale, and emerging diagnostic science that does not yet exist in public datasets.
  • Partner with clinical and medical teams to ensure scientific work is grounded in real health outcomes.

Minimum Qualifications:

  • Deep, demonstrated ML expertise in applied health AI, evidenced by publications, adopted systems, or both.
  • Hands-on track record with messy, high-dimensional real-world data, not only benchmark results.
  • Demonstrated judgement making dataset-level calls: when proprietary labelling is worth the investment versus when open data is good enough.
  • Academic relationships strong enough to attract named collaborators and candidates to Neko.
  • Track record operating as a senior contributor without final decision authority, comfortable at the table rather than leading it.
  • High agency, with a bias to contribute momentum in a fast-moving environment.
  • Skilled to represent Neko externally with the scientific community, regulators, or partners.

Preferred Qualifications:

  • Appetite and early aptitude for people leadership; this role has a path to building a small team as impact proves out.
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