Founding Applied Computer Vision Engineer (Identity Preservation, Pose Transfer & Character Consistency)
"Build something billions of people will use"
Billions of people take photographs. Almost everyone has experienced the same frustration: the moment happened, but the photograph did not capture them at their best.
We are building Spotted—a UK-based AI imaging company creating technology that turns ordinary phone photographs into extraordinary, professionally captured images.
This is not a learning role
We are looking for an exceptional senior applied computer-vision or generative-imaging engineer who has already worked on closely related problems—or who can demonstrate that they can solve this one quickly.
Please apply only if you can independently:
understand the problem from first principles;
evaluate existing methods honestly;
build and combine the right approaches;
produce a working demonstration quickly;
measure identity and geometry preservation properly;
show failures rather than hiding them;
turn an experimental workflow into defensible technology.
You will not receive a pre-written technical recipe. You will help determine what should be built.
The problem you will own
Our current workflow uses a generative image model to create alternate poses of a real person in the same scene. The recent composition and body pose may be excellent, but the generated face often becomes a slightly different person. It may look similar to the original subject while changing their underlying facial structure. Your job is to build a system that:
Retains the generated target pose, expression, gaze, clothing and scene.
Restores the real person’s identity and facial geometry.
Preserves the jaw, cheeks, eyes, nose, chin, facial outline, natural asymmetry and age cues.
Integrates the reconstructed face or head naturally with the target lighting and image quality.
Does not silently beautify, reshape or standardise the person.
Leaves the body, clothing, hands and background untouc