Are you interested in starting your career with a deep tech company working with leading Aerospace and Defence companies like Airbus, GKN, BAE Systems etc.?
Are you interested in decarbonising the manufacturing industry using innovative AI technology?
Do you enjoy working on cutting-edge, scalable technology in a team environment?
If the above questions excite you, then please continue reading!
About the role
At Intellium AI, we hire the best minds in technology to innovate and build solutions that our customers desperately want to adopt AI successfully within their businesses. We have built an Enterprise AI platform to give our customers the power of AI irrespective of their skill background.
You will be matched to a manager and mentor in your role. You will have the opportunity to perform a state-of-the-art literature review in the field of green and sustainable manufacturing and make an impact on the evolution of our products, as well as lead mission-critical projects early in your career. Your design, code, and raw smartness will contribute to solving some of the most complex technical challenges in the areas of automation, optimisation, scalability, and security.
Key job responsibilities
- Develop supervised and unsupervised machine learning models, for example, XGBoost, KNN etc.
- Develop deep learning models using Neural Networks, e.g. Auto Encoders, Generative Adversarial Networks (GANs), Federated Learning etc.
- Develop Explainable AI modules to present machine learning results to end users
- Implement optimisation algorithms using the trained machine learning (surrogate) models
- Develop uncertainty quantification modules to highlight the uncertainty in model prediction
- Implement cutting-edge AI algorithms from published scientific documents
- Write technical articles/blogs on industrial use cases
Qualifications
- Master’s in data science with a background in Engineering
- Mastery of Python programming language
- Strong written and verbal communication skills
- Basic working experience/knowledge in Unix/Linux environment
- Basic knowledge of containerised applications, for example, Docker
- Basic knowledge of GPU-based highly parallel software development
