NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence

JPMorgan Chase & Co.
Central London, W3 0BJ, United Kingdom
3 months ago
Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Lead
Education
Phd
Posted
11 Mar 2026 (3 months ago)

NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence

210667160

T09:27:16+00:00

London

Predictive Science

Full time

NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of Excellence

The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, large language models, and recommendation systems.

The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for machine learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.

Job Responsibilities

  • Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
  • Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, LLMs or recommendation systems
  • Produce outputs that lead to high-impact business applications, open-source software, patents, and publications in top AI/ML conferences and journals.
  • Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
  • Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business

Required qualifications, capabilities, and skills

  • Solid background in NLP and LLMs, and solid understanding of machine learning and deep learning methods
  • Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
  • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field
  • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
  • 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 problem

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 search/ranking, Reinforcement Learning or Meta Learning
  • Expertise in recommendation systems
  • 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

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 To learn about how we're using AI/ML to drive transformational change, please read this blog:

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.

#MLCOE_jobs

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.

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.


Related Jobs

View all jobs
Spotlight

Senior ML Compiler Engineer

Fractile Bristol, United Kingdom
Spotlight

Senior ML Runtime Engineer

Fractile London, United Kingdom

Lead Data Scientist

Yolk Recruitment Cardiff, Cymru / Wales, CF10 2AF, United Kingdom
£100,000 – £110,000 pa Hybrid

Data Scientist

Yolk Recruitment Cardiff, South Glamorgan, CF10 2AF, United Kingdom
£60,000 – £70,000 pa Hybrid

Lead ML Engineer

Harnham - Data and Analytics Recruitment Manchester, United Kingdom
£90,000 – £95,000 pa Remote

Lead ML Engineer

Harnham - Data and Analytics Recruitment Sheffield, United Kingdom
£80,000 – £90,000 pa Remote

Lead ML Engineer

Harnham - Data and Analytics Recruitment Newcastle upon Tyne, United Kingdom
£80,000 – £90,000 pa Remote

Lead ML Engineer

Harnham - Data and Analytics Recruitment Leeds, United Kingdom
£80,000 – £90,000 pa Remote

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.