Staff Applied Scientist in London

Overview

At Unlikely AI, 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.

• What You’ll Do
• 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.
• What We’re Looking For
• 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 Py Torch, HF Transformers, Tensor Flow, 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

• Use of Python libraries that encourage best practices such as pytest, pylint, black etc.
• Experience with symbolic reasoning engines and integration with neural networks.
• Strong technical writing skills as evidenced by relevant publications or blogs.
• Start-up experience.
• Git/Github
• Proficiency working with cloud platforms for deploying hybrid AI systems.
• Please see our Company Principles to understand the core things we value – in particular, we are looking for exceptional people who are willing to tackle some of the most difficult technical problems there are, in order to create something extraordinary with huge impact.
• Location

We are currently operating a hybrid scheme with a small office near Holborn tube station available to anyone who wants to work there.

We also have occasional team days where everyone meets face to face and days where people work heads down from home, communicating with colleagues using Slack and Zoom.

Compensation

Compensation will be through salary and generous share options.

The company has a tax-efficient EMI share option scheme set up (not available to larger companies) which allows us to provide real exposure to the success of the company without taxes being due when they are paid.

Equal Opportunities

We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves.

We, therefore, do not discriminate in employment based on gender, race, religion, sexual orientation, national origin, political affiliation, disability, age, marital status, medical history, parental status or genetic information.

Having a broad mix of people helps us to be the best we can.

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