Who We're Looking For
This Role
- Pre-processing and analyzing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.
- Developing and utilizing innovative deep learning models in combination with state-of-the-art optimization methods to predict and control the behaviour of physical systems.
- Taking full responsibility for the quality, accuracy and impact of your work.
- Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
- There is a requirement to travel to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you’ll collaborate closely with customers to build solutions on site.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
What we offer
- Equity options – share in our success and growth.
- 10% employer pension contribution – invest in your future.
- Free office lunches – great food to fuel your workdays.
- Flexible working – balance your work and life in a way that works for you.
- Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility.
- Enhanced parental leave – support for life’s biggest milestones.
- Private healthcare – comprehensive coverage
- Personal development – access learning and training to help you grow.
- Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.