At a Glance
- Tasks: Design and prototype AI solutions using cutting-edge generative AI technologies.
- Company: Aspect, one of London's largest property-maintenance teams with bold growth plans.
- Benefits: Gain hands-on experience, mentorship, and build a portfolio of real AI projects.
- Other info: Collaborative culture that values experimentation and your innovative ideas.
- Why this job: Join us to make a tangible impact with generative AI in a dynamic environment.
- Qualifications: Pursuing a Master's in Data Science or related field with strong Python skills.
The predicted salary is between 500 - 1500 £ per month.
About Us
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.
Essential
- 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
AI Engineer Intern employer: Aspect
Aspect is an excellent employer for pest control professionals, offering a dynamic work environment in Greater London where you can make a real impact on both residential and commercial properties. With competitive pay rates and the flexibility of self-employment, we prioritise your growth through ongoing training and support, fostering a culture of teamwork and innovation that empowers you to excel in your role.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer Intern
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Aspect!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Engineer Intern at Aspect.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Aspect.
✨Apply Directly through Our Website
When you find a suitable opening like AI Engineer Intern at Aspect, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI Engineer Intern
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Aspect, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Aspect. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Aspect
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Aspect!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
