Machine Learning Engineer (Defence - hiring mid to senior levels | 2yrs+)
Newcastle (on-site)
Defence Tech Start-up
Machine Learning Engineer (Defence Tech)
A growing defence‑tech consultancy is seeking Machine Learning Engineers of various levels and disciplines to work on advanced AI solutions and/or design and implement machine learning systems, including LLM applications within secure environments.
You’ll genuinely be working alongside some of the best engineers/teams in the country, solving problems no one else has before.
They are deliberately setting a very high bar, hiring engineers from top universities who are among the strongest technically in their field. The work is very problem-solving focused, small teams tackling complex systems, often working on completely new challenges every few months.
People we’re hiring for and value
- Enjoy working on challenging systems
- Are friendly
- Truly understand problem-solving principles
- Are adaptable and articulate
Machine Learning Engineer Responsibilities may include
- Applying machine learning fundamentals and statistical techniques
- Working with LLMs and transformer architectures
- Evaluating model performance and optimising inference
- Developing solutions for constrained or secure environments
- Supporting explainability, safety, and robustness of AI systems
- Integrating AI/ML components into applications and workflows
- Designing and implementing retrieval-augmented generation systems
- Evaluating LLM performance and mitigating failure modes
- Testing and debugging non-deterministic systems
- Assessing when AI vs deterministic approaches are appropriate
Machine Learning Engineer Requirements (it would be useful if you have some of the following experience - not all is required)
- Deep understanding of machine learning fundamentals
- Strong mathematics and statistics knowledge
- LLM principles and transformer architectures
- LLM performance evaluation and inference optimisations
- Developing modules for edge, constrained or air-gapped environments would be a plus
- Explainable AI or AI safety/security would be a plus
Applied AI overlap
- Integrating AI components into applications and workflows
- LLM evaluation, failure modes, and mitigation strategies
- Testing and debugging non-deterministic systems
- Retrieval-Augmented Generation
- Understanding of the risks and limitations of AI and where statistical models or deterministic logic would be more appropriate
- Understanding of core AI/ML concepts such as LLM architectures, ML models, and statistical methods
Additional Criteria
- STEM Degree from a leading university (2:1 or 1st class)
- Eligibility for UK SC-level security clearance
- Experience in defence or highly regulated environments is advantageous, but not required
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