Job Description
Metric has partnered with a VC-backed AI company working with leading retail and ecommerce brands to improve how their product data performs across search engines, generative answer engines, and AI-driven discovery systems.
They are looking for a Senior Machine Learning Scientist specializing in Search Engine Optimisation and Generative Engine Optimisation, applied through data, modelling, and experimentation.
What you will work on:
- Building algorithms that improve product visibility in generative search and answer engines
- Analysing search, clickstream, and system data to understand AI crawling and summarisation
- Applying NLP to model intent, relevance, and semantic signals used by LLMs
- Predicting the impact of technical optimisation changes on generative search performance
- Automating structured data and factual enrichment with engineering teams
- Running experiments to measure GEO and AEO impact versus traditional search
What they are looking for:
- 6+ years experience in Machine Learning, Applied Science, or Data Science
- Hands-on experience with NLP, LLMs, embeddings, and semantic search
- Understanding of search relevance and information retrieval concepts
- Experience working with large datasets using SQL and cloud data platforms
- Strong Python skills for data analysis (Pandas, NumPy) and ML (Scikit-learn, PyTorch/TensorFlow)
- Familiarity with SEO or search data APIs for programmatic analysis
Preferred skills:
- Experience optimising for generative or answer-based search systems (GEO/AEO)
- Experience running controlled experiments or A/B tests in search environments
- Experience working in a startup or high-growth product environment
This role is a great fit for someone who has already worked on SEO or search optimisation problems, and has taken a scientific, ML-led approach to improving visibility, attribution, and retrieval performance.