Senior AI Engineer, Personalization

Stealth AI Startup; Stockholms kommun; Presencial; SEK 1 100 000 - 1 600 000; Tempo integral

Resumo da oferta

Stealth AI Startup seeks a senior ML engineer to design, build, and deploy personalized recommendation systems at scale. You will work in a fast-paced, early-stage environment to turn research into production-grade solutions, focusing on real-time decisioning and user-centric experiences.

You will develop feature pipelines, experiment with contextual bandits or reinforcement learning, and implement robust evaluation and feedback mechanisms to improve model performance over time.

Qualificações

• MSc or PhD in a quantitative field with strong recommender systems background.
• Demonstrated ability to take a recommendation system from research to production.
• Experience with sequential modeling (recurrent/attention-based models) and production ML engineering.

Responsabilidades

• Build personalization and recommendation systems with real-time context.
• Design feature pipelines handling high-volume behavioral data with low latency.
• Scale cold-start to data-rich deployments without changing architecture.
• Implement exploration-exploitation frameworks (contextual bandits, online learning, RL).
• Create feedback/learning infrastructure translating user interactions into model improvements.
• Develop evaluation frameworks distinguishing genuine personalization from proxy metrics.

Formação académica

MSc in ML/CS/Statistics (top-tier university)

PhD in ML/CS or related field

Descrição da oferta de emprego

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

• 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

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
• 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
• Production ML engineering discipline; code that serves reliably in production, not only evaluates well in notebooks
• Demonstrated ability to take a recommendation system from research to production

Preferred Qualifications

• PhD in Machine Learning, Computer Science, or a directly related quantitative discipline; given significant weight in our assessment
• Research depth in recommendation, sequential modeling, or online learning
• Experience with privacy-preserving approaches to behavioral modeling
• 2–5 years of experience; exceptional graduates assessed on equal terms with experienced engineers
• A body of independent work; published research, open source contributions, or personal projects that demonstrate what you build without instruction

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.

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.