SENIOR AI ENGINEER - PERSONALIZATION

We are a well-funded, early-stage technology company on a mission to fundamentally redefine the way the world searches, discovers,

and transacts, built on a philosophy that puts the user first at every step.

The user is not simply a means of transaction. They are a valued participant whose data works for them, not against them,

enriching their world and their own experience within it, with them retaining full control.

The internet was built to inform the many, not to serve the individual. Platforms optimize for engagement, extraction, and

consumption at global scale. AI has made this model even more efficient, with the user still largely remaining the input, not the

full beneficiary.

The problem is not information. The world has never had more. The problem is that people give away a lifetime of data without

receiving the personalized experience it should enable.

• Highly ambitious and action-driven; you thrive under pressure and find genuine energy in working at the edge of what is

considered possible

• Capable of designing and building production-grade systems in a fourth of the time most experienced and “sane” professionals

would consider possible

• Build personalization systems that combine behavioral modeling, dynamic user representations, and real-time context-aware

content delivery

• Design and operate feature engineering pipelines that transform high-volume behavioral event streams into model-ready inputs

within the latency and reliability constraints

• Build recommendation systems that scale seamlessly from cold-start to data-rich production environments without requiring

architectural changes

• Implement exploration-exploitation frameworks such as contextual bandits, online learning, or reinforcement learning approaches

that continuously optimize content delivery without heavy offline retraining cycles

• Build feedback and learning infrastructure that translates user interactions into measurable model improvements on a continuous

basis

• Design evaluation frameworks capable of distinguishing genuine personalization quality from overfitting to easily measured

proxy metrics

• Deep theoretical and applied understanding of recommendation systems; has implemented methods from the literature and shipped

them to real users

• Experience with sequential modeling applied to user data; recurrent architectures, attention-based sequence models, or

equivalent

• PhD in Machine Learning, Computer Science, or a directly related quantitative discipline; given significant weight in our

assessment

• A body of independent work; published research, open source contributions, or personal projects that demonstrate what you build

without instruction

Expect the most talented, rigorous, and driven colleagues you have worked with; people who lift each other up and hold each other

to the highest standard. This company is driven by ideas and innovation, regardless of age, position, or background. The best

ideas must win and the people behind them recognized and rewarded.

A home for exceptional people and geniuses within their domain; those who have always known what they are capable of and have been

waiting for the environment to prove it to the world, whilst first being seen and supported by their coworkers.

We are an equal opportunity employer committed to building an inclusive, high-performance culture where everyone can do their best

work and reach their full potential. We welcome applicants of all backgrounds and do not discriminate on the basis of race, color,

religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, or any other characteristic

protected by applicable law.

To apply, send your CV/resume, LinkedIn profile, and a note on how and why you would like to contribute to our mission. Upon

initial acceptance, an online interview will follow shortly in Stockholm, Sweden.

Please note that all applications and interviews are conducted in English. Fluency in written and spoken English is a requirement

for all roles.