Senior AI Engineer, AI Lab

What You’ll Do

• 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 modelling
• 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 philosophical questions raised by AI‑generated content

The majority of roles operate on a hybrid working pattern, with 3+ days office attendance required.

• Highly competitive pension or 401(k) plan
• Private health insurance
• 24/7 access to counselling and wellbeing resources through an Employee Assistance Program
• Work From Anywhere program – up to 25 days per year from any location where you have the legal right to work
• Generous annual and parental leave
• Dedicated days off for volunteering and moving home
• Free access to all Economist content, including an online subscription, apps, podcasts, and more