Akkodis
Artificial Intelligence Engineer
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AI 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.
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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.
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Key skills
- Strong Python development.
- 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.
If you’re interested in developing production AI capabilities for complex autonomous systems, apply or get in touch to learn more.
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