Staff ML Research Scientist (m/f/d)

the company builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue.

Our two products, Playtime Arcade and the company Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising.

Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem.

Next-Gen Machine Intelligence for Scalable Discovery & Engagement

The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and the company Ads.

Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches—specifically generative approaches —to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation.

These frameworks scale the company's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users.

The team operates at the intersection of bleeding-edge R&D and high-scale production engineering, acting as the company’s internal science bar raiser and primary consulting layer for complex ML bottlenecks.

The stack is optimized for deep learning and heavy data throughput: Py Torch and (Ray/Hugging Face) for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads.

The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments.

Your Mission & Who We Are Looking For

• Ph D or equivalent research depth, with a track record of technical mentorship.

Ph D in CS, Statistics, Math, or Physics.

Publications in SIGIR, KDD, Neur IPS, or ICLR, and 5+ years building large-scale recommender systems in Ad Tech, e-commerce, or social.

You've owned architectural bets and had accountability for outcomes.

• You set the research direction.

You identify the highest-leverage problems at the intersection of generative AI and recommendation, define the multi-quarter research agenda, and align engineering and product leadership.

That means owning how Generative Retrieval, Deep Ranking, and Re-ranking evolve across a stack built on 770 million users' behavioral data.

• Deep expertise in Py Torch and large-scale model optimization.

Hands‑on with high‑concurrency optimization, quantization, and distillation — getting large generative models to run under extreme production constraints, not just in research environments.

• You are the company's deepest resource on generative recommendation.

You translate SOTA research into systems the company can ship, review architectural decisions across teams, and raise the ML quality bar company‑wide.

When there's a hard bottleneck, you're the first call.

• You grow the teams around you. You mentor senior and mid‑level scientists, lead architectural debates, and drive long‑horizon investments without needing a roadmap handed to you.

We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team.

What’s in It for You?

At the company, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech.

The systems you work on will reach hundreds of millions of users and power billions of decisions every day.

• Go Big. Own projects with impact on 770M users and push adtech boundaries.
• Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum.
• Be Direct. Solve problems openly and collaborate across teams.
• Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other.
• Have Fun. Celebrate wins, enjoy daily victories, and bring your energy.

We welcome applications from people who will contribute to the diversity of our company.

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