AI Engineer, AI Lab Commercial

We are an organisation that exists to drive progress. That's the “red thread” that connects everyone at The Economist Group (TEG). Our businesses share a devotion to innovation, independence and rigour in their fields of expertise. We empower people to understand and tackle the critical challenges and changes facing the world. Our analytical rigour, global expertise and evidence-based insights enable individuals and organisations to make sense of these shifts and chart a course through them.

We deliver analysis and insights in many formats to subscribers and clients in 170 countries through our four businesses, The Economist, Economist Impact, Economist Intelligence and Economist Education, which uphold our global reputation for excellence and integrity.

The Economist Group is a global media and information services company committed to championing progress. We equip individuals and organisations with expertise, insights, and perspectives to navigate change and drive growth.

This is a full-time role at the centre of our new AI Lab, a small team exploring how generative AI might shape the future of Economist journalism. This role will focus on building and fine-tuning LLM-powered systems with a particular focus on editorial tone, style transfer, retrieval workflows, and multimodal generation (especially audio).

You’ll ship products from zero-to-one and see your ideas directly influence how millions of readers interact with our journalism. If you enjoy working close to design, iterating fast, and building novel interactions across text, voice, and visuals, we’d love to hear from you. You'll be one of the first three engineers in a dedicated lab, working alongside the Tech Lead, Design Lead and Product Lead.

• Fine-tune large language models (LLMs) for style and tone alignment with The Economist’s editorial voice
• Design, curate, and manage datasets used for fine-tuning, including versioning and annotation workflows
• Build and evaluate RAG pipelines that incorporate retrieval from structured content
• Prototype and test TTS (text-to-speech) pipelines for use in audio-first products (leveraging tools like Eleven Labs, OpenAI TTS etc)
• Collaborate with infra, frontend, and design leads to ship internal tools and demos that explore GenAI capabilities
• Own quality evaluation pipelines (BLEU, ROUGE, editorial scoring, custom evals), including human-in-the-loop feedback loops
• Support product experiments where real-time generation, summarisation, or personalization are being tested
• Partner directly with journalists and editors to develop novel evaluation metrics that capture the nuances of The Economist's tone and style

• 3+ years experience building with LLMs or NLP pipelines (ideally hands‑on with OpenAI, Claude, Cohere, Gemini, Mistral, Hugging Face)
• Experience with supervised fine‑tuning (SFT), prompt tuning, or instruction tuning on proprietary datasets
• Strong understanding of fine‑tuning paradigms, from SFT to the principles behind RLHF/RLAIF preference modeling
• Strong Python skills, including working with Lang Chain, Hugging Face Transformers, and data pipelines (Pandas, DVC, Weights & Biases)
• Comfortable defining and tracking generation quality with eval metrics like BLEU, ROUGE, and building editorial‑specific evaluators
• Exposure to STT / TTS tools for prototyping (e.g., Whisper, Eleven Labs, Bark, etc.)
• Strong communication and collaboration mindset — able to work closely with editorial and product stakeholders
• Curious and exploratory — comfortable working in ambiguity and pushing the boundaries of GenAI capabilities

• Experience fine‑tuning models for style or persona (e.g. chatbots with specific character voices)
• Exposure to Lang Smith or similar observability tools for prompt / LLM testing
• Knowledge of voice synthesis, cloning, or emotion conditioning in audio pipelines
• Previous work in media, journalism, podcasting, or content production contexts
• Familiarity with multi‑modal generation (text + image + audio), or interest in pushing toward that frontier
• Contributions to open‑source LLM tools or libraries
• An interest in the ethical, editorial, and…