Lead Applied AI Engineer: NLP/LLM & Graphs (Production)

J.P. Morgan Asset Management; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

J.P. MORGAN is seeking an NLP / LLM Scientist – Applied AI ML Lead to advance the Machine Learning Center of Excellence. You will tackle NLP, LLMs, and recommendation systems with deep learning methods.

You will work with Business, Technology, Product, Legal, and Compliance to deploy robust ML solutions in production and contribute to publications, conferences, and open-source projects. The role emphasizes collaboration and innovation.

Qualifications

• Solid background in NLP and LLMs; deep learning methods.
• Published research in ML/ DL or RL at major conference/journal.
• PhD or MS with strong industry/research experience.
• Extensive experience with ML/DL toolkits (TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
• Ability to design experiments and evaluate metrics aligned with business goals.
• Hands-on experience building and deploying agentic AI / multi-agent systems in regulated environments.
• Experience with big data and clear communication of technical results.

Responsibilities

• Research new ML methods via independent study and conferences.
• Develop state-of-the-art models for NLP, LLMs, and recommendation systems.
• Produce outputs leading to business impact, open-source software, patents, and publications; collaborate across teams to productionize solutions.
• Advance large-scale ML frameworks to accelerate deployment across the business.
• Collaborate with Business, Technology, Product, Legal, Compliance, Strategy and Management.

Skills

NLP

LLMs

Deep learning

Research

Scientific thinking

Communication

Team collaboration

Problem solving

Education

PhD in a quantitative discipline

MS with significant industry/research experience

Tools

TensorFlow

PyTorch

NumPy

Scikit-Learn

Pandas

Job description

J.P. MORGAN is seeking an NLP / LLM Scientist – Applied AI ML Lead to advance the Machine Learning Center of Excellence. You will tackle NLP, LLMs, and recommendation systems with deep learning methods.

You will work with Business, Technology, Product, Legal, and Compliance to deploy robust ML solutions in production and contribute to publications, conferences, and open-source projects. The role emphasizes collaboration and innovation.