Machine Learning Engineer

Refine Search

Sectors Salary Job Type

Permanent

Contract

Back to search results

Job TypePermanent

Are you an experienced machine learning / artificial intelligence practitioner? Joining the Electronics UK business side of a world leading Aerospace and Defence company.. The successful candidates will take a prominent role in delivering world leading sensor solutions across a variety of military platforms in a collaborative, agile environment.

You role will be to lead the implementation of AI/ML technologies into specialist software products, these products are a major contributor to aircraft survivability and enhancing future mission effectiveness.

What you will do

You will lead the scoping, implementation and strategic planning of AI/ML technologies for incorporation into different sensor products.
You will identify opportunities within complex data sets and leverage industry leading COTS technologies to deliver advanced analytic capabilities to the forefront of Aircraft defensive systems.
You will support the development of early careers engineers leveraging your experience and skills to create a core AI/ML capability within the business.

What we are looking for

People with experience of and a passion for developing machine learning and artificial intelligence solutions.
You should have a degree level qualification (or equivalent) in mathematics, physics, computer science, engineering or a related discipline and a desire to learn and share knowledge with others.
Due to the nature of the tasks involved, you must be able to satisfy the necessary security clearance for the role and meet a minimum of 5 years permanent residency in the UK.

In addition you will be expected to have some of the following skills:

Strong numerical, analytic and problem solving skills for algorithm development.
Signal processing, image processing, data processing, high performance computing; or scientific or mathematical libraries for numerical computing, simulation or optimisation problems.
Programming in Python, Matlab or C/C++.
Machine learning frameworks such as Pytorch, Keras/Tensorflow.
Matlab Deep Learning framework.
Common neural network architectures.
Embedded systems, edge computing or cloud computing.
High performance computing hardware including parallel computing/multi-processing, GPU acceleration.
Software development lifecycle and Dev Ops.
Real-time systems with sensors, internet of things or imaging applications (infrared, Lidar, Radar, radio frequency).