Who We Are
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.
Our mission is underpinned by proprietary, patent-pending technology built on a novel engine and system.
The Problem You Will Be Solving
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.
People should not have to search. They should simply find.
Who You Are
Highly talented and motivated to build products with people, for people
You thrive in zero-to-one environments and find genuine satisfaction in creating from scratch
A fast-paced thinker with a relentless desire to learn, improve, and raise the standard around you
Able to inspire, elevate, and collaborate; you make the people around you better
A great communicator; you express complex ideas with clarity, precision, and confidence across all levels of the organization
Able to transform ideas into working systems and technical milestones with light speed and precision
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
What You Will Do
Design end-to-end machine learning architectures, including data pipelines, feature engineering, model training, real-time serving, and evaluation systems
Build scalable personalization and relevance systems that process high-volume, sequential behavioral data in real time to power context-aware content delivery at scale
Develop high-velocity model training pipelines capable of learning from large-scale heterogeneous datasets, enabling rapid experimentation while maintaining production-grade rigor and reliability
Design and operate low-latency model serving infrastructure that supports seamless version rollouts, traffic management, and feature transitions with zero user-visible disruption
Create comprehensive experimentation and evaluation platforms, combining offline metrics, online A/B testing, and integrated tooling to provide continuous, data-driven visibility into platform improvements
Establish ML engineering standards around code quality, reproducibility, monitoring, and incident response that will be inherited by the broader engineering team
Minimum Qualifications
MSc in Machine Learning, Computer Science, Statistics, or a directly related quantitative field from KTH, Chalmers, ETH Zurich, EPFL, or an institution of equivalent standing
3 or more years of industry experience designing and shipping production ML systems at scale; architectures you originated, not contributed to
Demonstrated experience working in or alongside early-stage, fast-moving technology companies; you understand what it means to build without a safety net
Deep expertise in at least two of: large-scale personalization, recommendation and ranking systems, sequential behavioral modelling, real-time ML serving, or privacy-preserving ML at the architecture level
Production software engineering discipline that extends well beyond model code; you design the systems beneath the ML layer, not only the models on top of it
Exceptional candidates with fewer years of industry experience will be considered where their research output, published work, or demonstrated systems constitute an equivalent body of evidence
Preferred Qualifications
PhD in Machine Learning, Computer Science, or a directly related field; given significant weight in our assessment
Prior experience as a technical lead, staff engineer, or principal engineer at a high-growth technology company or research institution
Background from a company known for world-class ML systems; Spotify, Klarna, Google, Meta, OpenAI, DeepMind or comparable
Research publications or substantive independent technical work in relevant technical areas
A track record of delivering complete, production-quality ML systems at a pace that clearly distinguishes you from peers
What We Offer
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.
Compensation includes an attractive salary and meaningful equity ownership for an early-stage startup.
Equal Opportunity
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.
Application
To apply, send your CV/resume, GitHub profile, LinkedIn profile, and a brief note on how and why you would like to contribute to our mission. Upon initial acceptance, an in-person 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.
All applications are treated with strict confidentiality.
