Covering more trades than anyone else, Aspect is one of London’s largest property-maintenance teams. We operate 24/7, helping thousands of residential and commercial customers every month. After 15 years of steady growth, we have bold plans to scale even faster over the next three years—and we’re harnessing generative AI to get there. If you’re excited by cutting-edge tech and real-world impact, join us at this pivotal moment.
The Role
We’re looking for an inquisitive, hands-on AI Engineer Intern (Generative AI / LLM / RAG) for a 4-month internship programme. You’ll join our data and product teams to design, prototype, and evaluate solutions that leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to improve customer experience, internal workflows, and decision-making.
Think: building chatbots that tap our knowledge base, fine-tuning models on call-centre transcripts, or creating smart agents that surface the right maintenance engineer in seconds. You’ll see first-hand how generative AI moves the needle for a growing business.
You Will
- Prototype RAG pipelines - set up vector stores, devise retrieval strategies, and iterate on prompts
- Fine-tune or adapt foundation models (e.g., Llama-3, GPT-4o) to company-specific data
- Build evaluation harnesses to measure accuracy, latency, and hallucination rates
- Work with Python, LangChain/LlamaIndex, Hugging Face, and cloud LLM endpoints (OpenAI, Azure AI, etc.)
- Collaborate with analysts, engineers, and ops teams to turn PoCs into deployable micro-services
- Present findings to stakeholders, translating technical insight into business value
- Contribute to best-practice docs on prompt engineering, model versioning, and AI governance
About You
You’re a problem-solver who loves experimenting, learning fast, and shipping usable prototypes. You pair solid theory with the scrappiness needed in a scale-up environment.
- Currently pursuing (or recently completed) a Master’s in Data Science, Machine Learning, AI, or similar
- Strong Python skills and experience with a modern ML/AI stack (PyTorch, Transformers, or equivalent)
- Familiarity with vector databases (FAISS, Pinecone, Qdrant, Chroma, etc.) and RAG concepts
- Ability to explain complex ideas clearly to non-technical audiences
- Curiosity about how AI can drive tangible business growth
Nice to Have
- Hands-on work with LangChain, LlamaIndex, or similar orchestration frameworks
- Knowledge of prompt-engineering techniques and evaluation metrics (BLEU, ROUGE, BERTScore, etc.)
- Experience deploying models on Azure, AWS, or GCP
- Understanding of MLOps tools (MLflow, Weights & Biases, GitHub Actions)
- Prior projects that show a creative application of generative AI (link or brief description)
What You’ll Gain
- Ownership of real AI projects that reach production users
- Mentorship from senior data scientists and engineers
- Deep exposure to LLM tooling, RAG architectures, and AI evaluation best practices
- A portfolio of deliverables demonstrating end-to-end generative-AI workflows
- A collaborative culture that encourages experimentation and values your ideas
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