Senior Applied AI Scientist (AI Learning)

Stack

Responsibilities

• ▹AI research and development: apply deep learning, NLP, LLMs and multimodal AI to build and optimise scalable machine learning solutions for personalised learning and AI tutors
• ▹Applied science execution: work on cutting-edge AI models, contributing to research, prototyping and deployment in production
• ▹Partner with scientists, engineers and product teams to deliver AI-driven solutions that improve learning experiences and business outcomes
• ▹Support and mentor junior scientists and engineers
• ▹Contribute to machine learning best practices: model architecture, research methodologies and deployment pipelines

Requirements

• ▹PhD in NLP, Machine Learning or a related field (or equivalent experience)
• ▹4+ years of industry experience focused on deep learning-based NLP applications
• ▹Strong proficiency in deep learning frameworks such as PyTorch or TensorFlow
• ▹Hands-on experience with cloud platforms (e.g. AWS, Google Cloud)
• ▹Ability to drive AI initiatives from research to production in a collaborative environment
• ▹Strong problem-solving skills and a track record of building impactful AI solutions
• ▹Passion for advancing AI-driven personalised learning experiences
• ▹Eagerness to work in a fast-paced, cross-functional setting

Nice to have

• ▹Experience with LLMs and retrieval-augmented generation (RAG)

Soft skills

What we offer

• ▹Open, collaborative, dynamic and diverse culture
• ▹Generous monthly allowance for lessons on Preply.com, learning and development budget and time off for self-development
• ▹Competitive financial package with equity, leave allowance and health insurance
• ▹Relocation package to the Barcelona hub
• ▹Access to free mental health support platforms
• ▹Gympass-partnered wellness and gym centres throughout Spain

About the company

Preply's AI Learning team builds the models and systems behind personalised learning paths and real-time feedback, using multimodal LLMs trained on video, audio and transcripts. The team works with product and engineering to bring research into production for features that reach millions of learners.