Senior Applied Scientist

At UnlikelyAI, we’re looking for a Senior Applied Scientist to join our Applied Science team. This is a high-impact individual contributor position. 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. Why Join Us? Team – You’ll join a world-class group of smart, collaborative people who are deeply motivated by challenge. We move fast, support each other, and genuinely enjoy the ride. Vision – Our mission is to build a novel neurosymbolic AI framework that unlocks new frontiers in explainability and reasoning — and you’ll be instrumental in shaping that. Tech – Our technology is truly novel. You’ll get the chance to explore original ideas, tackle unsolved problems, and help define new best practices in an environment where creativity and rigour go hand in hand. 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. 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: 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.