Machine Learning Scientist

Amentum is currently recruiting for a Machine Learning (ML) Engineer/Scientist to develop and improve ML methods/applications - particularly those involving Deep Learning (DL) - within the Advanced Reactors team. The spectrum of work of the team is very broad with a strong focus on computational analysis in support of various nuclear reactor types, both fission and fusion. We are looking for an enthusiastic and innovative person to further develop our capability in ML methods to solve complex scientific and engineering problems and grow our technical offering in this rapidly evolving field.

This role will present excellent opportunities for the continual development of skills and experience in ML, particularly as applied to nuclear engineering; also, the potential to lead technical developments and collaborations, and the teams responsible for their implementation.

The role will be based at our Birchwood office with the opportunity to travel to client sites, as required. Some home / remote working is also available, and consideration will also be given in respect to part time & flexible working hours.

Key responsibilities:

• Developing ML applications, typically in the context of nuclear science and engineering

• Cooperation with customers to plan ML applications and gather training data

• Development of code (e.g. in Python/PyTorch/TensorFlow) for data processing and training of Artificial Neural Networks (ANNs)

• Working together with the team and customers to identify opportunities for exploitation of ML approaches

• Providing training in the area of ML to members of the team

Essential Qualifications/Experience

• An undergraduate degree in mathematics, physics, engineering, or a related quantitative discipline

• Proficiency in Python programming and associated libraries (e.g., numpy, pandas, scikitlearn, matplotlib)

• Familiarity with DL frameworks such as PyTorch or TensorFlow.

• Familiarity with DL architectures including Convolutional Neutral Networks and Transformer Networks

• Ability to think innovatively, solve complex problems, and be able to quickly absorb new technical skills

• Self-motivated and with the ability to work both independently and collaboratively

Desirable Qualifications/Experience

• A postgraduate degree in ML with a first degree in physics or related disciplines

• Experience of developing ML models for scientific/engineering applications

• Experience with uncertainty quantification methods and how they can be applied to ML systems

• Knowledge of advanced ML/DL systems such as Reinforcement Learning (RL), Physics Informed Neural Networks (PINNs), Automated Machine Learning (AutoML), and AI trustworthiness/explainable AI

• Knowledge of training/deploying ML models using cloud compute platforms (e.g. AWS, Azure, GCP)

• Experience of contributing to nuclear science/engineering projects

• Journal/conference publications relating to ML and/or nuclear science

Our Culture:

Our values stand on a foundation of safety, integrity, inclusion and diversity. We put people at the heart of our business, and we genuinely believe that we all succeed by supporting one another through our culture of caring. We value positive mental health and a sense of belonging for all employees.

We aim to embed inclusion and diversity in everything we do. We know that if we are inclusive, we’re more connected, and if we are diverse, we’re more creative. We accept people for who they are, regardless of age, disability, gender identity, gender expression, marital status, mental health, race, faith or belief, sexual orientation, socioeconomic background, and whether you’re pregnant or on family leave. This is reflected in our wide range of Global Employee Networks centered on inclusion and diversity.

We partner with VERCIDA to help us attract and retain diverse talent. For greater online accessibility, please visit www.vercida.com to view and access our roles. As a Disability Confident employer, we will interview all disabled applicants who meet the minimum criteria for a vacancy. We welcome applications from candidates who are seeking flexible working and from those who may not meet all the listed requirements for a role.

If you require further support or reasonable adjustments with regards to the recruitment process (for example, you require the application form in a different format), please contact the team