Machine Learning Engineer

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 Machine Learning Engineer, you’ll scale our personalization systems, optimizing large-scale training pipelines, building high-performance vector stores, and enabling scientists to bring advanced AI models to production. More specifically you will:

• Develop and optimize distributed training pipelines for large-scale deep learning models.
• Build and maintain high-performance vector storage systems.
• Drive hyperparameter optimization workflows to accelerate experimentation and improve model performance.
• Collaborate with Applied Scientists to translate research prototypes into production-ready pipelines.
• Write clean, efficient, and maintainable code with a focus on performance and scalability.
• Strong software engineering background, with fluency in Python and/or Rust.
• Experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Good understanding of machine learning concepts and workflows.
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• Ability to collaborate closely with scientists and translate research needs into engineering solutions.

Curiosity, adaptability, and eagerness to learn new tools and techniques. Strong communication skills in English. Flexibility to work from anywhere across Europe. Budget for learning and training, attend events and conferences.