Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Scientists

AWE
Tadley
8 months ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Scientist, Personalisation

Machine Learning Engineer - GenAI

Machine Learning Engineer, Model Customization, Generative AI Innovation Center

Machine Learning Engineer (SC Cleared)

Machine Learning Engineer – Insurance

Machine Learning Engineering Manager

Machine Learning ScientistsClosing Date: 7th February 2025Location: RG7 4PR, located between Reading and Basingstoke, with free onsite parking.Due to the classified nature of the work involved, there are limited opportunities to work from home in this role. It is anticipated that the successful candidate will spend the majority of their time working on site at AWE Aldermaston.Packages: Experienced Machine Learning Scientist (PHD or graduates with post-grad experience): £39,500 - £47,500 (depending on your suitability and level of experience)Senior Machine Learning Scientist (qualifications coupled with experience in industry): £52,000 - £62,000 (depending on your suitability and level of experience). A relocation package may be available (terms and conditions apply.Working pattern: AWE operates a 9-day working fortnight. We will consider flexible working requests so that your work may fit in with your lifestyle. Just let us know your preferred working pattern on your application.Let us introduce the roleDo you enjoy designing and developing Machine Learning models? What if you could work with remarkable people on extraordinary things?What if your role was mission critical contributing to produce something a little bit special?For 75 years, AWE Nuclear Security Technologies has been at the forefront of nuclear weapons and security research.Machine Learning has the potential to impact every part of our mission: we have exciting opportunities for Machine Learning Scientists to join our team. We need your knowledge and skills in Machine Learning Operations, model development and deployment.At AWE you will be able to train your models at scale on some of the UK's largest supercomputers, leveraging our long history and bright future in high performance computing.Who are we looking for? We do need you to have the following: Degree in a STEM or IT discipline, equivalent NQF level 6 qualification or equivalent experienceKnowledge of data analytic methods and visualisation in languages such as PythonAbility to integrate and work well in a team and support or take the technical lead in projectsWhilst not to be considered a tick list, we'd like you to have experience in some of the following:Structured approach to problem solvingAbility to convey complex and highly technical issues to diverse audiencesFamiliarity with common Python libraries for data management, statistical analysis, machine learning and visualisationKnowledge of a specific discipline in Machine learning, e.g. NLP, LLM, images, emulation…Familiarity with software development lifecycleLinux/HPC computer environments.You'll need to have the ability to work calmly and constructively in a priority changing environment and be able to manage your own workload. You will also have initiative, enthusiasm, a flexible approach, and ability to work to tight deadlines.Some reasons we think you'll love it here: AWE has wide range of benefits to suit you. These include:9-day working fortnight - meaning you get every other Friday off work, in addition to 270 hours of annual leave. Market leading contributory pension scheme (we will pay between 9% and 13% of your pensionable pay depending on your contributions).Family friendly policies: Maternity Leave - 39 Weeks Full Pay and Paternity Leave - 4 Weeks Full Pay.Opportunities for Professional Career Development including funding for annual membership of a relevant professional body.Employee Assistance Programme and Occupational Health Services.Life Assurance (4 x annual salary).Discounts - access to savings on a wide range of everyday spending.Special Leave Policy including paid time off for volunteering, public service (including reserve forces) and caring.The 'Working at AWE' page on our website is where you can find full details in the 'AWE Benefits Guide'.Next steps: Everyone who works at AWE brings unique skills and perspectives to the table. We recognise that great people don't always 'tick every box'. That's why we focus on your potential, your fit with our values, your transferable skills as well as your experience. Even if you don't meet every point above, but you feel that this role and AWE are a great fit for you, please go ahead and apply, we'd love to receive your application.Important things you need to know:We encourage you to apply promptly to avoid disappointment if applications are high and the role therefore closes.You will need to obtain and maintain the necessary security clearance for the role. This will be funded by AWE. The nature of our work does mean you need to be a British Citizen who has been resident in the UK for the past 5 years in order to apply for SC clearance and 10 years for DV. We want you to feel comfortable and able to shine during our recruitment process. Please let us know on your application form if you need any adjustments/accommodations during the process. Our interviews typically take place over Teams and for most roles are a 1 stage process.#LI-KT

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.