AI/ML Researcher
Role details
Job location
Tech stack
Job description
You will have the opportunity to work with colleagues across the capability in multi-disciplinary teams and to work on a wide range AI topics for customers across the defence, security and commercial sectors as well as on internal BAE Systems AI programmes. You will also have the opportunity to maintain strong links with academic partners and SME partners as well as to grow technical research areas of interest to you. You will have strong experience of working in projects on topics such as NLP, LLM applications/approaches (e.g. Agentic AI), knowledge graphs and/or graph machine learning and with a vision on how to develop solutions for practical applications of ML in these domains. You should have existing skills in Machine Learning (ML), will need to be a proficient programmer in Python, with extensive experience in the use of libraries, tools (docker, git) and frameworks (e.g. LangChain/LangGraph or similar) to support efficient development. Typical Responsibilities:
- Propose and lead novel research in given topic areas.
- Lead technical delivery of small project teams. Prepare and deliver technical reports, technical proposals and supporting material.
- Develop prototypes and proof of concept demonstrators.
- Take ownership of tasks in projects and deliver to challenging standards.
- Effectively present results to both technical and non-technical audiences., Here you'll build a career with purpose and limitless possibilities. With lifelong learning and meaningful work - this is a place where you can grow your career with confidence and be empowered to be your best. You'll be recognised for your contribution and enjoy rewards tailored to what's most important to you and your family - support for your financial and personal wellbeing, as well as a balanced lifestyle. In an environment embracing sustainable ways of working and with a strong sense of shared purpose, our supportive culture is a place you can feel you belong and proud of the difference you make. A place where everyone can thrive. We're committed to building an inclusive workplace where everyone feels valued and supported. We know that a diversity of backgrounds, perspectives and experiences strengthens our teams and is vital to the work we do. We welcome applications from all candidates and give full, fair and open consideration to everyone. If you require any reasonable adjustments during the recruitment process, please contact our recruitment team to discuss any further support you may need. Connect with us at baesystems.com/connect Please be aware that many roles at BAE Systems are subject to both security and export control restrictions. These restrictions mean that factors such as your nationality, any nationalities you may have previously held, and your place of birth can restrict the roles you are eligible to perform within the organisation. All applicants must as a minimum achieve Baseline Personnel Security Standard. Many roles also require higher levels of National Security Vetting where applicants must typically have 5 to 10 years of continuous residency in the UK depending on the vetting level required for the role, to allow for meaningful security vetting checks.
Requirements
- You will have a PhD in a relevant topic.
- Experience in software development in Python
- Experience with at least one ML framework: TensorFlow, Pytorch.
- Experience working with LLMs, knowledge graphs, or graph machine learning
- Of particular interest are candidates with the following experience (evidenced by a track record of publications, industry experience, open-source available code or equivalent academic work):
- Natural Language Processing, including Information extraction, text-mining and entity linking. Experience with modern (e.g. transformer-based) NLP models is desirable but not essential.
- Application of LLMs to Defence problems.
- The taxonomy of Graph Machine Learning tasks and experience in using graph ML in applied or foundational settings.
- Graph-structured data, designing and utilising relational and graph databases, and knowledge of graph algorithms.
Desirable Knowledge, Skills and Experience:
- Familiarity with knowledge representation, ontology design and semantic or LLM based reasoning
- Experience with one or more graph machine learning packages (PyTorch-Geometric, PyKeen etc.) and knowledge graph toolkits (Neo4j)