Staff Applied Scientist, UnlikelyAI

• Deep learning expertise with significant industry experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation
• Demonstrable experience leading in an individual contributor capacity—setting technical direction, influencing others, and delivering high-impact work without direct management responsibilities
• Experience mentoring and coaching colleagues, offering guidance on both technical and professional development
• Experience with Python and common ML Frameworks like Pytorch, HF Transformers, Tensorflow, JAX
• Track record working as an independent contributor capable of end-to-end development with demonstrable experience in utilising and deploying transformer models
• Deep knowledge of machine learning fundamentals and cloud experience
• Enthusiasm to learn and get up to speed with cutting-edge technologies which you may not already be deeply familiar with
• Excellent verbal and written communication skills with a proven track record of mentoring and coaching others
• Capable of working collaboratively and proactively in a fast-paced environment with scientists, engineers, and non-technical stakeholders

Desirable

• At UnlikelyAI, we’re looking for a visionary Staff Applied Scientist to play a key leadership role in our Applied Science team and across the company
• This is a high-impact individual contributor position with mentoring and coaching responsibilities — ideal for someone who combines technical depth with a passion for helping others grow
• You’ll help drive the end-to-end lifecycle of projects: from identifying opportunities in literature, through proof-of-concept, to real-world production
• Your work will sit at the cutting edge of Machine Learning and reasoning systems, with a particular focus on neurosymbolic AI, complex planning, and fully explainable architectures
• Convert cutting-edge research in neurosymbolic AI into real, production-grade language generation systems
• Design and experiment with hybrid neurosymbolic architectures that challenge current thinking in reasoning and planning
• Lead applied research projects end-to-end: from ideation and literature review to prototyping and deployment
• Write high-quality, robust code that integrates neural and symbolic components
• Collaborate with a team of scientists and engineers, articulating complex ideas clearly to technical and non-technical audiences
• Analyse and inspect large-scale datasets to support neural training and symbolic extraction