Machine Learning Engineer - Satellite Systems
Newton Colmore is working with a leading technology innovator in Cambridge, and we are looking for a machine learning engineer to join their research and development team.
As a machine learning engineer in this company, you will hold responsibility for the design and development of new ideas, from initial eureka moment and concept through to manufacture. You will be taking your work through the whole product life cycle. This role will test your deep learning experience and give you exposure to the broad ML development cycle: data I/O, cleaning and preparation, rapid code prototyping, iterating model designs and deploying and packaging code into products ready for deployment.
The company have developed a rapid approach to design and implementation, which you will be utilising to its fullest capacity, delivering step changes in technology as quickly as possible.
This company design and manufacture several complex instruments and devices for the defence and security industries, including advanced communications and satellite technology, RADAR systems and other devices that utilise computer vision to track incoming threats. This means that you will need to obtain UK security clearance to be considered for this exciting role.
You will be bringing with you a passion for deep learning and solving problems, coupled with strong academics. To be successful in this role you will also need experience with libraries like TensorFlow and sci-kit learn, and have knowledge of neural network architectures and exposure to emerging technologies; GANs, LLMs, RL or XAI.
The company are offering tailored packages for the right engineer, which includes a performance bonus, free lunches, and market leading pension plan. They can also offer you career progression and foster an environment that encourages collaboration, learning and self-development.
If you would like to find out more about this opportunity than go ahead and make an application and a member of our team will be in touch to talk through the role further
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