Improbable - Machine Learning Research Scientist

Improbable is dedicated to building powerful technology designed to help solve previously impossible problems and enable the creation of new realities. In gaming and entertainment, Improbable unlocks truly next-generation gameplay through virtual worlds of unprecedented scale, persistence and richness. In other industries, we hope to help answer critical questions through simulations that could lead to a better functioning world. 

Our platform, SpatialOS, lets developers transcend the limits of regular computation, allowing swarms of servers running in the cloud to cooperate in order to simulate worlds far larger and more complex than any single server could.

We are a British technology company proudly building a diverse workforce, driven by a shared desire to improve and achieve extraordinary things. We’re crafting technology for the future and fostering a problem-solving culture that embraces innovation through iteration and experimentation.

Your Mission

As a Machine Learning specialist you will sit in our research group, developing and implementing probabilistic inference algorithms for our latest platform. You will also provide support and consultation to our project teams, helping to design, build and deploy bespoke models which provide insight into our clients’ most challenging problems.

We work extensively with graphical models, especially Bayesian networks and hidden Markov models, combining data-driven methods with more hypothesis-driven modelling. There is a strong research element to the role particularly in prototyping and evaluating novel methods - or established methods in novel applications. Much of this might be tackled independently or as part of a small, close-knit team of researchers and prototypers. 

When supporting our project teams you will work with software engineers, data scientists and modellers to architect a model & data strategy that will tackle our clients’ problems. You may also take ownership of aspects of quality assurance of the project output.

We support academic partnerships, publishing and are focussed on building a world-class team. You can read about the engineering culture of the division here.

Some parts of our work are open sourced. Check out to experiment.


  • Demonstrated research background (likely PhD) in a scientific or mathematical field, ideally with a computational element, such as Physics, Data Science, Statistics or Mathematics.
  • Applied academic or industrial experience in: 
  • Graphical models - especially Bayesian networks
  • Probabilistic inference
  • Machine learning and deep learning techniques
  • Gaussian processes
  • Hidden Markov models
  • Relevant post-doctoral or industrial experience which demonstrates client-facing and/or project-delivery skills.
  • Pragmatic coding ability - with fluency in at least one relevant programming language and the ability to adapt to a variety of languages and to implement algorithms.
  • Enthusiastic about continuously improving and rapidly developing new competencies.

Equal Opportunity

The best ideas are often the least expected and require new ways of thinking; that’s why our teams at Improbable are made up of an incredible range of talented people. Improbable is proud to be an equal opportunity employer. We do not discriminate based on race, ethnicity, colour, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.

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