Job Description

An innovative AI software company is seeking a Senior Machine Learning Engineer to take ownership of a production-scale information-extraction platform. This is a hands-on role focused on building high-accuracy NLP and LLM-powered systems capable of extracting structured information from large volumes of complex technical documents.

You'll have end-to-end ownership of model development, evaluation, and deployment, working on challenging document-understanding problems while helping to shape the next generation of AI-powered products.

What You'll Be Doing

• Design, build and optimise production-grade NLP and machine learning pipelines.
• Develop high-performance information extraction systems capable of processing complex, long-form documents.
• Build and improve hybrid AI solutions combining traditional NLP techniques, rule-based systems and Large Language Models (LLMs).
• Fine-tune machine learning models to improve accuracy, scalability and production performance.
• Define evaluation strategies, quality metrics and annotation methodologies to continually improve model performance.
• Process and extract insights from large-scale structured and unstructured datasets.
• Work closely with engineering and product teams to deliver production-ready AI capabilities.

What We're Looking For

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence or a related discipline.
• 4+ years of experience building and deploying production NLP or Machine Learning systems.
• Strong experience with Named Entity Recognition (NER), entity extraction and information extraction techniques.
• Experience developing document understanding or long-document processing solutions.
• Solid software engineering skills with Python and modern machine learning frameworks.
• Experience building scalable ML pipelines for production environments.
• Strong problem-solving skills and the ability to independently own technical solutions.

Desirable Experience

• Experience combining traditional NLP techniques with Large Language Models (LLMs).
• Familiarity with prompt engineering, retrieval-augmented generation (RAG) or agentic AI frameworks.
• Experience processing large-scale technical or enterprise document collections.
• Knowledge of model evaluation, annotation workflows and continuous model improvement.