Machine Learning Engineer / Applied Scientist (NLP / LLMs / Search) London (Hybrid) | Up to £110k
Python | NLP | LLM | Machine Learning | Elasticsearch | OpenSearch | PyTorch | Tensorflow | AWS | RAG |
This is for a organisation is building a platform designed to help users navigate and analyse large volumes of complex technical and legal text using a combination of machine learning, search technologies and LLM-driven approaches.
They are looking for someone to play a key role in shaping how their systems retrieve, rank and interpret data at scale. The position sits across applied machine learning, NLP and search, with a strong focus on modern LLM-driven workflows.
The role is hands‑on but also carries significant ownership, with responsibility for influencing technical direction across areas such as semantic search, vector retrieval, ranking optimisation, and retrieval‑augmented pipelines.
Responsibilities include:
- Improving relevance and ranking across large‑scale search systems
- Designing and optimising LLM‑powered pipelines
- Working with hybrid and vector‑based retrieval approaches
- Developing NLP components for structured and unstructured text
- Contributing to scalable ML infrastructure and cloud‑based pipelines
The environment is primarily Python‑based, leveraging frameworks such as PyTorch or TensorFlow, search technologies like Elasticsearch/OpenSearch, and AWS for infrastructure.
They are interested in candidates who:
- Have experience building and deploying ML systems in production
- Bring a background in NLP and/or LLM‑based applications
- Are comfortable working with search or retrieval systems
- Have strong Python skills in a commercial environment
- Can take ownership of technical decisions and direction
The package offers a salary of up to £110k, 25 days holiday, and a hybrid working model (3 days onsite in London), along with flexibility and support for ongoing development.
Python | NLP | LLM | Machine Learning | Elasticsearch | OpenSearch | PyTorch | Tensorflow | AWS | RAG |
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