Your role is to lead the development and engineering of machine learning algorithms from concept to production. The research and tools you develop will be central to our ground-breaking technology demonstrators, ensuring that Improbable’s decision support tools, training systems and digital twins embody robust and cutting-edge science.
The Research team brings together experienced researchers and software engineers from multiple disciplines interested in improving the performance, validity, richness and effectiveness of simulations of complex systems. We regularly publish, and work closely with both industry and academic collaborators; this year, two of our researchers received Royal Society awards for their collaboration with leading academics from the Turing Institute, and Leeds, Exeter and Warwick Universities.
Areas for Impact
- Lead the development and engineering of novel machine learning algorithms, working closely with research scientists
- Work with other research scientists and engineers to pursue research and development towards our strategic objectives. This requires translation of ambitious but often vague objectives into concrete proposals, with a realistic assessment of the necessary resources and expected outcomes
- Understand deeply and take ownership of the vision for next-generation software for planning and training for defence and security – to save lives and public funds. This means thinking creatively about customer problems, and often taking a novel perspective on established fields
- Contribute to the strategy and execution of Research at the team level; set goals, mentor junior engineers, and drive change to support the team’s impact and growth
We’d like to hear from you if you identify with the following:
- A track record of delivering software projects in an academic or industry setting, experience scaling and deploying ML models is desirable
- A demonstrable interest and experience in machine learning, particularly probabilistic deep learning, e.g. VAEs, GANs, normalising flows, (deep) Gaussian processes
- PhD in Computer Science or related field
- High level of proficiency in Python
- Experience with deep learning and/or probabilistic programming libraries in Python, e.g. Pytorch, Pyro
- Experience with a low level language like C, C++ etc.
- A track record of relevant research as evidenced by publications, patents and/or conference talks
Nb: While we think the above experience could be important, we can’t predict the future and so we’re keen to hear from applicants that believe they have valuable experience. If you identify with the team & mission, but not all of the suggestions, then please still apply
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About Us
Improbable is determined to foster an environment where people can do their best work and feel like they belong. We believe a healthy culture, strong values and contribution from a diverse range of individuals will help us to achieve success.
We do not discriminate based on race, ethnicity, gender, ancestry, national origin, religion, sex, sexual orientation, gender identity, age disability, veteran status, genetic information, marital status or any other legally protected status.
Life at Improbable
Diversity, inclusion & belonging.
