Real-Time ML Applied Scientist (Remote in Europe)

Albatross AI; France; Remoto; EUR 90.000 - 130.000; Tempo pieno

Vantaggi offerti da questo lavoro

Learning budget and conference support

Remote across Europe

Descrizione del lavoro

Albatross is seeking an Applied Scientist to advance real-time machine learning, personalization and search. You will design state-of-the-art algorithms and translate them into product-ready capabilities that power decision-making over billions of interactions.

You will prototype novel approaches in deep learning, reinforcement learning, and LLMs, collaborate with data scientists and engineers, and maintain rigorous code quality.

Competenze

• 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.
• Publications in top ML conferences are a plus.
• Strong communication and collaboration skills in English.

Mansioni

• Design, implement, and improve ML algorithms powering real-time recommendations and search.
• Prototype and validate novel approaches in deep learning, reinforcement learning, and LLMs.
• Collaborate with Data Scientists and Engineers to generalize solutions and build tooling.
• Maintain high code quality and experimentation discipline.
• Publish technical work and represent Albatross in the ML research community.
• Drive innovation in transformer architectures, multimodal embeddings, and scalable retraining.

Conoscenze

Python

PyTorch

TensorFlow

JAX

ML deployment

Publications

Formazione

PhD in ML/CS/Math

Descrizione del lavoro

Albatross is seeking an Applied Scientist to advance real-time machine learning, personalization and search. You will design state-of-the-art algorithms and translate them into product-ready capabilities that power decision-making over billions of interactions.

You will prototype novel approaches in deep learning, reinforcement learning, and LLMs, collaborate with data scientists and engineers, and maintain rigorous code quality.