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Principal Machine Learning Scientist, Enterprise

Data Science @ London

Our Purpose

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 expert, you will lead our ML R&D team driving the research, development and implementation of probabilistic inference algorithms on our platform. We work extensively with graphical models, especially Bayesian networks and hidden Markov models, combining data-driven methods with more hypothesis-driven modelling.

As the Principal Scientist you will;

  • lead the Machine Learning research agenda for our distributed inference platform alongside the Simulation research group and supported by the core software engineering team.
  • have autonomy to set the research direction of the group, balancing near-term and long-term research objectives
  • build and lead a group of ML researchers and growing the team’s responsibilities as you deem fit, within the overall goals of the business
  • own a budget for hiring, travel, conferences, academic outreach and other research-related costs.
  • grow our academic network and research partnerships, including monetary spend and long-term strategic input
  • provide overall expertise around our ML strategy, helping to shape and drive this strategy and inform senior decision makers

  • In addition to this, as a specialist you would provide expertise and thought-leadership within the company. This involves keeping up-to-date with a diverse body of cutting-edge research, designing and prototyping pioneering new technical approaches and rapidly developing expertise in new subject areas to support new research directions and projects.

    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.

Competencies

  • Recognised research background (likely PhD) in a scientific or mathematical field, ideally with a computational element, such as Physics, Data Science, Statistics or Mathematics.
  • Extensive academic or industrial experience with; Graphical models - especially Bayesian networks, Probabilistic inference, Machine learning and deep learning techniques, Gaussian processes, Hidden Markov models
  • Experience leading research teams and working with product and engineering teams to drive
  • 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.
  • Enthusiasm to coach and develop more junior scientists and build understanding of ML techniques across the wider division.



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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