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JPMorganChase

Applied AI ML Lead Engineer- (NLP/LLM/Graph)

London
Posted 14 days ago
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Job Description

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
  • 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
  • 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
  • Drive Firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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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
  • Hands-on experience building and deploying agentic AI / multi-agent systems within regulated or compliance-driven environments
  • 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 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 (MLCOE) 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.

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For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe. To learn about how we're using AI/ML to drive transformational change, please read this blog: https://www.jpmorgan.com/insights/technology/technology-blog?source=cib_di_jp_aBtechblog102

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.

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Skills

Natural Language Processing
Large Language Models
Machine Learning
Deep Learning
Recommendation Systems
Data Science
TensorFlow
PyTorch
NumPy
Scikit-Learn
Pandas
Reinforcement Learning
A/B Experimentation
Big Data
Analytical Thinking
Cloud-Native Deployment

Location

London, England, United Kingdom

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