Role overview
Founded by design and gaming veterans, we’re a Nordic startup creating a new category where interior design meets games.
We’re backed by some of the biggest names in the industry (from Supercell, King, and Small Giant Games), and we’ve put together an extraordinary team with deep roots in games, UX, and tech. We move fast and care deeply about what we build. No fuss, just a tight team making something beautiful together.
Now we’re looking for someone just as sharp and self-driven, who’s excited to help shape what we’re building.
What we're looking for
You’ll be hands-on from day one building our own models - taking them from idea to real behavior - and playing a crucial role in creating our proprietary AI design system: a modular interior-design intelligence. AI sits at the core of what we do, and in our small, senior team you’ll collaborate across disciplines and directly shape how our AI behaves and what we ship.
Experience developing and evaluating models end-to-end, including data preparation and feature design
Experience in data analysis, model diagnostics, and interpretability
Strong experience with Python
Ability to run, deploy, and fine-tune models, including optimising training and inference
Practical mindset - you build systems meant for real-world use, not academic demos
Self-directed, collaborative, and comfortable in a fast-moving startup environment
Scene understanding, similarity models, segmentation, auto-tagging, or embeddings
Cloud platforms (especially GCP)
Retrieval systems or generative AI frameworks
Procedural generation techniques and algorithm design
Computer vision, including both classical image processing techniques and ML-based approaches
How We Work
This role is based in Stockholm, home to our studio. We work in a hybrid setup - balancing remote work with regular time together in the studio. We value flexibility, but also believe great things happen when we spend time together. We’re not able to support relocation at this stage, so the role requires you to already be based locally.