Albatross AI
Data Scientist
Albatross AIGermany11 hours ago
Full-timeRemote FriendlyOther
Location

Remote in Europe.

Albatross

At Albatross, we're building the second pillar of AI: a perception layer that understands how users actually experience content, in real time. Trained on live user interactions, Albatross learns and reasons on the fly. Our technology powers real-time, in-session discovery by adapting to evolving user interests, in real-time. We have raised significant funding and our platform already operates at scale, with billions of events being processed and hundreds of millions of predictions served.

The Role

As a Data Scientist, you will design and deploy machine learning models that power real-time personalization for our customers. You will own defined workstreams of ML projects end-to-end, and you will work closely with Applied Scientists and Engineers to translate product and customer needs into scalable ML solutions. More specifically, you will:

  • Design and implement machine learning models for ranking, recommendation, and personalization
  • Define feature engineering pipelines and modeling strategies for customer use cases
  • Train, evaluate, and deploy models using our internal ML tooling and infrastructure
  • Own project workstreams from data preparation through production deployment
  • Collaborate with Applied Scientists to integrate new algorithms into production systems
  • Contribute improvements to internal ML tooling and experimentation infrastructure
  • Monitor model performance and iterate based on real-world feedback

Requirements

  • Bachelor's degree in Machine Learning or STEM
  • Strong background in machine learning, statistics, or data science
  • Solid programming skills in Python
  • Experience training and deploying ML models in production environments
  • Familiarity with ML frameworks such as PyTorch, TensorFlow, or JAX
  • Experience working with large-scale datasets and feature engineering pipelines
  • Ability to work independently on moderately complex ML problems
  • Strong communication skills in English

Nice to Have

  • Experience with recommender systems, ranking models, or search
  • Experience with large-scale experimentation and evaluation pipelines
  • Familiarity with learning-to-rank models, bandits, or reinforcement learning
  • Experience working with cloud environments such as AWS, GCP, or Azure

Benefits

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

Key Skills

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