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AI Researcher

Job in Reading, Berkshire, RG317, England, UK
Listing for: Thales
Full Time position
Listed on 2026-09-01
Job specializations:
  • IT/Tech
    AI Business & Operations, AI Engineer (Applied/Software), AI Evaluation, Data Scientist
  • Research/Development
    AI Business & Operations, AI Evaluation, Data Scientist
Job Description & How to Apply Below
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…
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