Machine Learning Engineer – Defence Sector – Cambridge)

Machine Learning Engineer - Defence Sector - Cambridge A growing organisation within the Defence Sector, based in Cambridge, is currently seeking a skilled Machine Learning Engineer or Artificial Intelligence Engineer to contribute to the ongoing development of defence, security, and intelligence technologies. This is an expanding organisation offering intriguing career development opportunities based on success. You will work on a variety of projects, ranging from small individual initiatives to large ongoing projects, where you will collaborate with mechanical engineers, electronics engineers, inventors, scientists, and other industry experts. Given that you will be working on cutting-edge technologies with potential applications in corporate and national security measures, the ability to obtain security clearance is necessary. Ideally, you will have experience in Machine Learning or Artificial Intelligence projects spanning several years. While experience in the defence sector would be highly advantageous, it is not a strict requirement. What makes this organisation truly fascinating is its structure, which enables you to tackle some of the world's most intriguing problems without the bureaucratic hurdles often encountered in larger organisations. It is expected that you hold a degree that has prepared you for a role in Machine Learning or Artificial Intelligence. In addition to working on highly challenging and captivating projects, you will receive a competitive salary, bonuses, pension benefits, complimentary meals, health insurance, ongoing skills training, and other outstanding perks. If you seek daily challenges and the opportunity to work on projects at the forefront of the ML/AI field, we encourage you to apply now, as we anticipate significant interest in this role. Newton Colmore Consulting is a specialist recruitment company within the Medical Devices, Scientific Engineering, Scientific Software, Robotics, Data Science, Healthcare Communications, Science, Electronics Design, New Product Design, Human Factors, Regulatory Affairs, Quality Assurance, and Field Service Engineering sectors.

#J-18808-Ljbffr