Artificial Intelligence Engineer

Location: Bristol, Crawley, Cheadle or Glasgow

Working pattern: Hybrid

Akkodis is looking for an experienced AI Engineer to join a growing centralised AI team within the defence sector , developing secure and responsible AI solutions for autonomous and safety-critical systems.

Working within a multidisciplinary team of software engineers, data engineers, architects, domain experts and cyber-security specialists, you’ll take AI capabilities from initial concept through to production deployment.

The role

• Design, develop and evaluate AI and machine-learning models.
• Work across computer vision, deep learning, time-series analytics, NLP and autonomy.
• Build model-training and evaluation pipelines, including preprocessing, feature engineering and experiment tracking.
• Package and deploy models through secure APIs and production services.
• Define performance metrics, monitoring, feedback loops and drift-detection processes.
• Apply responsible-AI principles covering explainability, robustness, safety and bias.
• Support proof-of-concepts, customer demonstrations and technical workshops.
• Develop reusable AI frameworks, templates and reference implementations.

Required experience

• Five or more years delivering AI and machine-learning solutions.
• Experience taking AI projects from concept through to production deployment.
• Background within defence, aerospace, rail, medical or another safety or mission-critical environment.
• Specialist experience in computer vision, deep neural networks, time-series analytics or autonomy.
• Experience working within multidisciplinary engineering teams.
• Strong technical documentation and stakeholder communication skills.
• ROS 2 or similar robotics and autonomy frameworks.
• PyTorch, TensorFlow, Scikit-learn, Hugging Face and OpenCV.
• Pandas, NumPy and SQL.
• MLflow, Weights & Biases or similar experiment-tracking tools.
• Docker, FastAPI, ONNX, TorchScript or gRPC.
• MLOps, DevOps, Git and cloud deployment across AWS, Azure or GCP.
• Understanding of GPU acceleration and CUDA.

Experience with C++, safety-critical software development, AI governance or large-scale data initiatives would be advantageous.

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