Role: Machine Learning Engineer
Duration: Initial 6-12 months
Clearance Required: eDV
A leading client within the UK defence sector is currently seeking several experienced Machine Learning Engineers to join their advanced AI and data science division. Offering the chance to contribute directly to the UK's national defence capability while working at the cutting edge of applied AI.
The successful candidate will join a multidisciplinary team focused on developing and deploying machine learning models across various complex defence use cases, ranging from autonomous systems and surveillance technologies to predictive analytics and decision-support platforms.
Key Responsibilities:
1. Designing and implementing robust ML models suited to real-time or mission-critical defence environments
2. Processing and analysing complex datasets, including geospatial, signals, or operational intelligence data
3. Collaborating closely with software engineers, data scientists, and defence stakeholders to ensure scalable and secure system integration
4. Conducting rigorous testing, validation, and documentation of all ML models in line with regulatory and operational standards
5. Staying current with emerging AI/ML techniques and assessing their applicability to defence applications
6. Strong background in machine learning, data science, or AI, with a degree in a related field
7. Solid programming skills in Python and proficiency with libraries such as TensorFlow and PyTorch
8. Demonstrated ability to build and optimise ML pipelines from prototype to deployment
9. Understanding of algorithm performance in constrained or sensitive environments
10. Prior experience within the defence, aerospace, or national security sectors
11. Familiarity with computer vision, signal processing, or natural language processing
12. Exposure to MLOps, edge computing, or synthetic data generation
13. Knowledge of government or MOD procurement and technical frameworks is an advantage
If you are interested in the above position, please contact James Chapman at 07903 438136 or email [emailprotected] (even if you don't have a CV yet, I'd like to speak with you!).
#J-18808-Ljbffr