Artificial Intelligence Engineer

About the Company

Thales UK is committed to delivering high-impact AI capabilities across its businesses and to customers, enhancing the quality of offers, winning new business, and improving customer satisfaction.

About the Role

As part of a growing software and AI team in CortAIx Factory, the AI Engineer will collaborate with product owners, domain experts, data engineers, and software engineers to turn business problems into robust, secure, and scalable AI solutions.

Responsibilities

• Translate business needs into AI solution designs, clear requirements, and measurable success criteria.
• Design, implement, and evaluate ML/AI models (e.g., classical ML, deep learning, computer vision, NLP/LLMs, time-series).
• Build robust training and evaluation pipelines, including data preprocessing, feature engineering, augmentation, and experiment tracking.
• Ensure Responsible AI practices: model robustness, safety, explainability (e.g., SHAP/LIME), bias assessment, and alignment with MOD/regulatory requirements.
• Package AI models as secure services/APIs and collaborate with software engineers to productionise, monitor, and continuously improve models.
• Define operational metrics and feedback loops for model performance, data quality, and drift; support post-deployment reviews.
• Write secure, high-quality production code, unit/integration tests, and conduct peer code reviews.
• Create reusable AI components, templates, and reference implementations; contribute to the internal catalogue of capabilities.
• Support bids, PoCs, demos, and stakeholder workshops; communicate technical concepts to non-technical audiences.
• Work with data engineers and architects on data acquisition, labelling strategies, integration of third-party data, and data quality management.
• Participate in agile threat modelling and vulnerability management for AI features; adopt best practices for secure AI.
• Horizon scan for major AI technology trends; run trials and share best practices to accelerate responsible adoption.

Qualifications

• 5+ years’ experience delivering AI/ML solutions in complex, safety- or mission-critical domains (e.g., defence, aviation, rail, medical, or similar).
• Proven track record of taking AI projects from discovery through model development to production handover, with measurable outcomes.
• Significant hands-on experience in at least one area: deep neural networks, computer vision, or time-series analytics.
• High-quality technical documentation and stakeholder communication.
• Collaboration within cross-functional engineering teams.

Required Skills

• Strong Python programming skills; proficiency with modern software engineering practices (testing, code quality, CI).
• Expertise in ML/DL algorithms and techniques for supervised, unsupervised, and, where relevant, reinforcement learning.
• Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision.
• Experiment tracking and reproducibility tools (e.g., MLflow, Weights & Biases).
• Data wrangling and analysis (Pandas, NumPy, SQL); familiarity with Spark or similar is a plus.
• Model optimisation and deployment fundamentals: ONNX, TorchScript, FastAPI/gRPC; GPU acceleration (CUDA basics desirable).
• Responsible AI and security awareness: explainability, privacy-preserving methods (e.g., differential privacy, federated learning), adversarial robustness.
• Proficient with Git and collaborative development workflows.
• Awareness of Agile and DevOps principles; ability to work effectively with MLOps for production deployment.
• Knowledge of cloud AI services (AWS/Azure/GCP) and containers (Docker) is desirable.

Preferred Skills

• Governance of architecture or detailed designs throughout the project lifecycle.
• Experience with large-scale data initiatives, data labelling strategies, and data quality management.
• Familiarity with MLOps practices and cloud platforms for AI deployment.
• Contributions to open-source AI projects, publications, or patents.

Pay and Compensation

Competitive salary based on experience and qualifications.

Equal Opportunity Statement

Thales UK is committed to diversity and inclusivity in the workplace, ensuring equal opportunities for all candidates.

Job Details

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology and Engineering

Industries: Defense and Space Manufacturing, Medical Equipment Manufacturing, and Aviation and Aerospace Component Manufacturing

Location: Crawley, England, United Kingdom

• 5+ years’ experience delivering AI/ML solutions in complex, safety- or mission-critical domains (e.g., defence, aviation, rail, medical, or similar).
• Proven track record of taking AI projects from discovery through model development to production handover, with measurable outcomes.
• Significant hands-on experience in at least one area: deep neural networks, computer vision, or time-series analytics.
• High-quality technical documentation and stakeholder communication.
• Collaboration within cross-functional engineering teams., * Strong Python programming skills; proficiency with modern software engineering practices (testing, code quality, CI).
• Expertise in ML/DL algorithms and techniques for supervised, unsupervised, and, where relevant, reinforcement learning.
• Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision.
• Experiment tracking and reproducibility tools (e.g., MLflow, Weights & Biases).
• Data wrangling and analysis (Pandas, NumPy, SQL); familiarity with Spark or similar is a plus.
• Model optimisation and deployment fundamentals: ONNX, TorchScript, FastAPI/gRPC; GPU acceleration (CUDA basics desirable).
• Responsible AI and security awareness: explainability, privacy-preserving methods (e.g., differential privacy, federated learning), adversarial robustness.
• Proficient with Git and collaborative development workflows.
• Awareness of Agile and DevOps principles; ability to work effectively with MLOps for production deployment.
• Knowledge of cloud AI services (AWS/Azure/GCP) and containers (Docker) is desirable.

Preferred Skills

• Governance of architecture or detailed designs throughout the project lifecycle.
• Experience with large-scale data initiatives, data labelling strategies, and data quality management.
• Familiarity with MLOps practices and cloud platforms for AI deployment.
• Contributions to open-source AI projects, publications, or patents.

Competitive salary based on experience and qualifications.

Thales UK is committed to delivering high-impact AI capabilities across its businesses and to customers, enhancing the quality of offers, winning new business, and improving customer satisfaction.