Job Description

Location

Remote, right to work and travel in Europe.

Albatross

At Albatross, we are reinventing user engagement. Through advanced AI-driven personalization, we generate compelling user experiences that increase conversions and loyalty. We have the resources to build the most advanced foundational models for personalization, powered by a highly qualified team and guided by expert founders.

The Role

As an Applied Scientist at Albatross, you will help push the boundaries of real-time machine learning, personalization and search. You will design state-of-the-art algorithms and turn them into product-ready capabilities that power decision-making across billions of interactions. More specifically you will:

Design, implement, and improve the ML algorithms that power our recommendation and search engine. Prototype and validate novel approaches in areas such as deep learning, reinforcement learning and LLMs. Collaborate with Data Scientists and Engineers to generalize solutions and contribute to shared tooling. Maintain a high standard of code quality and experimentation discipline. Publish technical work and help represent Albatross in the ML research community and ensure our approach remains ahead of the curve. Work backward from product goals to guide the development of algorithmic solutions. Drive innovation in areas like AutoML, semantic embeddings, scalable retraining, and search.

Requirements

PhD in Machine Learning, Computer Science, Mathematics, or a related field. Proven experience in developing and shipping ML models in production. Strong Python skills and experience with ML frameworks such as PyTorch, TensorFlow, or JAX. Experience reading and implementing ideas from academic papers. Understanding of algorithms for search, ranking, recommendation, or representation learning is a plus. Publications in top ML or data science conferences (e.g. NeurIPS, ICML, KDD, RecSys, SIGIR) are a plus. Strong communication skills

in English

and collaboration skills.

Benefits

Flexibility to work from anywhere across Europe. * Budget for learning and training, attend events and conferences.