Senior Applied Scientist

As a Senior Applied Scientist joining Unlikely AI, you will be working the full project lifecycle: from literature to POC to production. You will have a key role in delivering products, starting with literature review, creating proof of concepts applying the latest Machine Learning techniques, collaborating with colleagues to implement and test your ideas, and helping deliver your solutions to production. The main areas of focus will be in neurosymbolic AI, complex reasoning and planning for fully explainable AI systems. 

Unlikely AI is a deep tech startup working to create a world where highly intelligent automated systems enable humanity to flourish and benefit us all. We are pioneering transformative technology aimed at making Artificial Intelligence more accurate, trustworthy and safe. By taking a contrarian approach, we believe our technology can solve some of the most pressing problems facing the industry. Based in London, the company was founded by William Tunstall-Pedoe, best known for his key role in the creation of Alexa following the acquisition of his first start-up by Amazon in 2012.

Why Join Us?

Team - We have a world-class team of intelligent, focused, collaborative people. We're ambitious, move fast and have a lot of fun while doing it.

Vision - We have a huge vision for the future. This offers a unique opportunity to work on the foundational layers of AI but, unlike many other companies, we're not just scaling LLMs, we're focussed on a novel neuro-symbolic approach.

Tech - You'll work with our novel and cutting-edge tech. Driving this forward involves solving some exciting challenges, so our team has the freedom to be creative and explore innovative ideas in an environment where our technology is evolving and maturing.

What You’ll Do:

Convert cutting-edge research in neurosymbolic AI and transform it into tangible, impactful language generation products.

Design, build, and experiment with hybrid neurosymbolic systems to push the boundaries of what’s possible in language generation.

Drive the design, development, and execution of high-impact scientific research projects.

Code for Impact: Write robust software, integrating neural and symbolic components for deployment in real-world production systems.

Collaborate & Communicate alongside a team of brilliant minds, articulating complex solutions with clarity and precision.

Analyse & inspect large scale datasets for both neural training and symbolic extraction.

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.

Required:

5+ years of hands-on experience in deep learning with deep knowledge of machine learning fundamentals.

Strong coding skills in Python and familiarity with one or more deep learning frameworks (e.g, PyTorch, TensorFlow.

Enthusiasm to learn and get up to speed with cutting-edge technologies which you may not already be deeply familiar with.

Ability to communicate complex research both written and verbal.

Familiarity with cloud platforms such as AWS and GCP.

Proficiency in data analysis techniques.

Use of Python libraries that encourage best practices such as pytest, pylint, black etc.

Desirable:

Experience utilising & deploying transformer models

ML Ops

Docker, K8s

Start-up experience

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.