AI Engineer

KEY RESPONSIBILITIES:
• Translate business and operational requirements into AI solution designs and measurable outcomes.
• Develop, train and evaluate AI and Machine Learning models across areas such as computer vision, autonomy, large language models and predictive analytics.
• Design and maintain robust data processing, training and evaluation pipelines.
• Apply Responsible AI principles, ensuring model robustness, explainability, security and compliance.
• Work closely with software engineers to deploy AI capabilities into production environments.
• Define and monitor model performance metrics, data quality indicators and model drift measures.
• Produce high-quality, secure and maintainable code following software engineering best practices.
• Generate technical documentation including architecture designs, model reports and implementation guidance.
• Develop reusable AI components and frameworks to accelerate future programme delivery.
• Support customer demonstrations, proof-of-concepts, technical workshops and bid activities.
• Collaborate with data engineers, architects and cyber security specialists to develop integrated
solutions.
• Evaluate emerging AI technologies and promote continuous improvement and innovation.
 

ESSENTIAL SKILLS & EXPERIENCE:
• Strong Python development experience within commercial or industrial environments.
• Experience developing AI and Machine Learning solutions using frameworks such as PyTorch,
TensorFlow or Scikit-Learn.
• Knowledge of autonomy frameworks such as ROS2 or equivalent technologies.
• Experience working with Computer Vision, Deep Learning, NLP/LLM or Time-Series Analytics
solutions.
• Strong understanding of data analysis and manipulation using tools such as Pandas, NumPy
and SQL.
• Experience deploying AI models into operational environments.
• Understanding of Responsible AI principles, model explainability and AI security
considerations.
• Experience using Git and modern software development practices including testing and
continuous integration.
• Knowledge of Agile development methodologies and DevOps/MLOps principles.
• Strong stakeholder engagement and communication skills with both technical and nontechnical
audiences.
• Degree, Master's qualification or equivalent experience in Artificial Intelligence, Software
Engineering, Data Science or a related discipline.
• Eligible to obtain UK Security Clearance (SC).
 

DESIRABLE SKILLS:
• Experience with MLflow, Weights & Biases or similar experiment-tracking tools.
• Experience with Spark or large-scale data processing platforms.
• Knowledge of ONNX, TorchScript, FastAPI or gRPC.
• Experience deploying AI solutions within Azure, AWS or Google Cloud environments.
• Experience using Docker and containerised deployment approaches.
• Experience developing software in C++ within safety-critical environments.
• Experience defining solution architectures or technical governance.
• Familiarity with large-scale data management and data-labelling strategies.
• MLOps experience supporting production AI deployments.
• Contributions to open-source projects, technical publications or patents.
• Relevant AI, cloud or Agile certifications.