Applied AI ML Engineer Director - NLP / LLM and Graphs

Fairygodboss; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

JPMorgan Chase is seeking an Applied AI ML Director - NLP/LLM and Graphs within the Machine Learning Centre of Excellence (MLCOE). You will apply advanced ML methods to NLP, graph analytics, speech analytics and time series, collaborating with business, technology, legal, and control partners to deploy production-ready solutions.

The role emphasizes leadership, hands-on DL, experimentation, research and sharing knowledge; PhD or MS with substantial experience required, and strong communication

Qualifications

• PhD in a quantitative discipline or MS with substantial industry/research experience.
• Strong background in NLP, LLM and graph analytics; hands-on ML/DL.
• Experience building agentic AI / multi-agent systems in regulated environments.
• Ability to design experiments and evaluate model performance with business goals.
• Excellent written and spoken communication to explain results to technical and business audiences.

Responsibilities

• Develop state‑of‑the‑art ML models for NLP, speech analytics, time‑series or recommendations.
• Collaborate with Business, Technology, PM, Legal, Compliance, Strategy and Business Management to deploy in production.
• Lead, mentor, and inspire a team of AI engineers.
• Drive firm‑wide initiatives with large‑scale ML frameworks.
• Research new ML methods through study, conferences, experimentation and knowledge sharing.

Skills

NLP & LLM

Graph analytics

Deep learning

Experiment design

Communication

Team leadership

Education

PhD in quantitative discipline

MS with significant experience

Tools

Python

TensorFlow/PyTorch

Big data platforms

Job description

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As an Applied AI ML Director - NLP / LLM and Graphs within the Chief Data & Analytics Office, Machine Learning Centre of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, graph analytics, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Deep Learning with hands‑on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.

Job Responsibilities

• Develop state‑of‑the‑art machine learning models to solve real‑world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time‑series predictions or recommendation systems
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
• Lead, mentor, and inspire a team of AI engineers, fostering a culture of excellence, innovation, and continuous learning
• Drive Firm wide initiatives by developing large‑scale frameworks to accelerate the application of machine learning models across different areas of the business
• Research and explore new machine learning methods through independent study, attending industry‑leading conferences, experimentation and participating in our knowledge sharing community

Required qualifications, capabilities, and skills

• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with significant years of industry or research experience in the field.
• Solid background in NLP, LLM and graph analytics and hands‑on experience and solid understanding of machine learning and deep learning methods
• Hands on experience building agentic AI / multi‑agent systems within regulated or compliance‑driven environments
  Recent hands‑on experience training, deploying models and pipelines
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals, with a focus on agentic systems and LLM evaluation
• Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
• Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail‑oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities , and skills

• Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
• Knowledge in graph integration with LLM, Reinforcement Learning or Meta Learning
• Experience with A/B experimentation and data/metric‑driven product development, cloud‑native deployment in a large scale distributed environment and ability to develop and debug production‑quality code
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal

About MLCOE

The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi‑disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting‑edge techniques in disciplines such as Deep Learning and Reinforcement Learning

For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe.

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first‑class business in a first‑class way approach to serving clients drives everything we do. We strive to build trusted, long‑term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.