Applied Scientist

Key Skills

AWS, Deep Learning, Docker, Effective communication skills, Google Cloud Platform (GCP), Machine learning techniques, MLOps tools, Python Programming, Science, TensorFlow

Job Description

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.

The company has raised a large ($20m) seed round reflecting the excitement investors have in the technology, team and potential of the business. We are looking to build a world-class technology team to realise the extraordinary possibilities of what we are doing.

As an 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 role is not limited to a specific field, but our current areas of interest include LLMs and Reinforcement Learning.

As an Applied Scientist working for Unlikely AI, you will:

Convert cutting edge research into real products

Design, build and experiment with cutting edge technologies

Drive the design, development, and execution of self-driven research projects

Write software that is built and deployed in production systems

Communicate complex solutions to colleagues

Analyse & inspect large scale datasets

Required:

2+ years of hands-on experience in deep learning

Deep knowledge of machine learning fundamentals

Strong coding skills in Python, including the use of pytorch or tensorflow

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

Strong verbal and written communication skills

Cloud (AWS, GCP)

Data analysis skills

Desirable:

Experience utilising & deploying transformer models

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

ML Ops

Docker, K8s

Start-up experience

Please note this role is not a pure research role and does not involve the creation of academic literature, but you should be very comfortable with reading and utilising academic papers and applying these concepts in your work.

Location:

We are based in London. After two years of operating completely remotely during COVID, we are now operating a hybrid regime 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.