Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build cutting-edge AI systems for content and audio experiences.
- Company: Globally recognised media and information business with a start-up vibe.
- Benefits: Competitive salary, hybrid work model, and innovative projects.
- Other info: High-autonomy environment with opportunities for rapid prototyping.
- Why this job: Join a dynamic team shaping the future of AI-native experiences.
- Qualifications: Experience in LLM systems and a passion for multimodal AI.
The predicted salary is between 100000 - 120000 £ per year.
Do you want to help build the next generation of AI-native content and audio experiences? Have you built LLM systems where output quality, tone, and trust genuinely mattered? Are you ready to work on multimodal AI products spanning text, voice, and conversational interfaces?
A globally recognised media and information business is building a brand-new internal AI Lab focused on next-generation AI-powered consumer experiences. This is a small, high-autonomy innovation team operating like a start-up inside an established international organisation. The team is exploring how conversational AI, retrieval systems, audio experiences, and multimodal generation can reshape how users interact with content and information products.
You’ll work closely with engineering, product, and design stakeholders on genuinely greenfield AI systems. This Senior AI Engineer role is focused on building production-grade LLM systems across fine-tuning, retrieval, summarisation, evaluation, and audio-first AI experiences. It’s a hands-on role with strong ownership and the opportunity to influence the technical direction of a newly formed AI Lab.
Key Responsibilities- Build and deploy production-grade LLM systems
- Design and optimise RAG and retrieval workflows
- Fine-tune models for tone, style, and output quality
- Develop audio-first AI products using TTS/STT workflows
- Build multimodal AI experiences across text, voice, and search
- Create evaluation frameworks for hallucination and response quality
- Prototype and iterate rapidly in a greenfield environment
- Salary: Up to ~£120k base
- Working model: Hybrid (3+ days/week in London)
- Stack: Python, HuggingFace, LangChain, RAG, multimodal AI, TTS/STT, evaluation frameworks
- Sponsorship: To be confirmed
Interested? Please apply below.
Applied Scientist - Content LLMs & Audio AI in City of London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist - Content LLMs & Audio AI in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working with LLMs and audio AI. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with LLM systems and audio experiences. This could be a game-changer during interviews, proving you’ve got what it takes.
✨Tip Number 3
Prepare for technical interviews by brushing up on relevant concepts. Be ready to discuss your experience with Python, HuggingFace, and multimodal AI. We want to see your passion and expertise shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Applied Scientist - Content LLMs & Audio AI in City of London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and content creation shine through. We want to see how your experiences align with our mission to build innovative AI-native products. Share specific examples of your work with LLM systems and how you’ve tackled challenges in this space.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Applied Scientist role. Highlight relevant skills like fine-tuning models and developing audio-first AI products. We love seeing candidates who take the time to connect their background with what we’re looking for!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that make it easy for us to see your qualifications. Use bullet points where appropriate and avoid jargon unless it’s relevant to the role. Remember, clarity is key!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter. We can’t wait to hear from you!
How to prepare for a job interview at Harnham
✨Know Your LLMs
Make sure you brush up on your knowledge of large language models (LLMs) and their applications. Be ready to discuss specific projects you've worked on, especially those that involved fine-tuning models for tone and style. This will show your depth of understanding and hands-on experience.
✨Showcase Your Multimodal Experience
Since the role involves multimodal AI products, prepare examples of how you've integrated text, voice, and audio in past projects. Highlight any work with TTS/STT workflows and how you approached building user-friendly experiences across different formats.
✨Demonstrate Problem-Solving Skills
Be ready to tackle hypothetical scenarios during the interview. Think about how you would design retrieval workflows or evaluate response quality. This is your chance to showcase your analytical skills and innovative thinking in a greenfield environment.
✨Engage with the Team's Vision
Research the company’s current AI initiatives and be prepared to discuss how your skills align with their goals. Show enthusiasm for working in a start-up-like team within a larger organisation, and express your ideas on how you can contribute to shaping the technical direction of the new AI Lab.