AI Researcher

Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. AI Researcher Reading (RG2 6GF) - Hybrid Primary Purpose of the Role: To conduct high-impact AI research that develops novel, trustworthy and operationally relevant AI capabilities across Thales UK businesses and for our customers, increasing the quality of our offers, winning new business, strengthening technical differentiation, and improving customer outcomes. As part of the growing software, AI and research capability in cortAIx Factory / cortAIx UK, the AI Researcher will collaborate with AI engineers, AI assurance specialists, human-machine teaming researchers, product owners, domain experts, data engineers and software engineers to turn complex operational and business challenges into validated AI research outcomes, proofs of concept and transferable technical capability. The role will contribute novel AI methods, research assets, technical reports, publications, invention disclosures and reusable experimental approaches to Thales UK’s internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used transversally throughout the business. We are interested in people with a background of both conduct research and delivering across a diverse range of products or industries. We are looking for those who can undertake the research but also understand how to translate this into product. Highly advantageous if you’ve supported or led bids/bid requirements. Key Responsibilities and Tasks: Conduct applied and experimental AI research to solve complex customer and business problems across defence, aerospace, cyber security, rail, critical national infrastructure and related domains. Develop state-of-the-art AI/ML solutions, proofs of concept and research prototypes using real-world data and operationally relevant problem statements. Investigate, design, implement and evaluate advanced AI methods, including but not limited to deep learning, multimodal AI, self-supervised learning, foundation models, generative AI, computer vision, NLP/LLMs, time-series analytics and reinforcement learning where relevant. Translate business and customer needs into clear research questions, experimental plans, technical requirements and measurable success criteria. Design robust evaluation methodologies, including baselines, benchmarks, ablation studies, uncertainty assessment, robustness testing and performance measurement against operationally meaningful metrics. Collaborate with AI V&V, AI Assurance, Human-Machine Teaming and Applied AI groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency, fairness, privacy, security and alignment with MOD, regulatory and Thales governance requirements. Create proofs of concept, publications, invention disclosures, patents, technical reports and reusable research assets around advanced AI topics such as multimodal learning, self-supervised learning, foundation models and human-AI collaboration. Package research outputs in a form that enables transition to AI engineering teams, including demonstrator code, model cards, experiment reports, design notes and handover documentation. Support bids, PoCs, demos, customer workshops, innovation campaigns and stakeholder briefings by communicating research concepts and outcomes to technical and non-technical audiences. Work with data engineers, architects and domain experts on data acquisition, labelling strategies, synthetic data approaches, integration of third-party data and data quality management. Horizon scan for major AI research and technology trends, assess relevance to Thales markets, run trials and share best practices to accelerate responsible adoption. Skills, experience and qualifications required Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience. Relevant subject areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Engineering, Physics or a related technical discipline. Strong Python programming skills; proficiency with modern software engineering and research practices, including testing, code quality, reproducibility and collaborative development. Experience conducting AI/ML research or advanced AI development in complex technical environments, preferably including defence, aviation, rail, cyber security, safety-critical, mission-critical or similarly regulated domains. Expertise in ML/DL algorithms and techniques for supervised, unsupervised, self-supervised and, where relevant, reinforcement learning. Proven ability to take AI research from problem framing through experimental design, model development, evaluation and prototype demonstration. Hands-on experience in at least one advanced AI area such as deep neural networks, computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial robustness and secure AI. Scientific and technical writing skills, including preparation of technical reports, research papers, invention disclosures, model cards and experiment reports. Demonstrable experience producing high-quality technical documentation, research outputs, model evaluations or stakeholder briefings. Interpersonal Skills Ability to engage and influence diverse stakeholders, including Product Engineering Leaders, Customers, Design Authorities, Project Management, IS/IT, research partners and academic collaborators. Highly effective in a matrix-based organisation; a collaborative team player who drives outcomes while maintaining scientific rigour. Excellent communication skills; able to explain complex AI research concepts clearly to technical and non-technical audiences. Curious, creative and intellectually rigorous, with the ability to challenge constructively and develop novel solutions to ambiguous problems. Encourages an open environment where ideas are shared, technical debate is welcomed and innovation thrives. Desirable PhD or equivalent research experience in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Engineering, Physics or a related discipline. Peer-reviewed publications, patents, invention disclosures, open-source contributions