Applied AI ML Director - NLP / LLM and Graphs in London

Applied AI ML Director - NLP / LLM and Graphs in London

London Full-Time 100000 - 130000 € / year (est.) No home office possible
hackajob

At a Glance

  • Tasks: Lead innovative AI projects using NLP, LLM, and graph analytics to solve real-world challenges.
  • Company: Join J.P. Morgan, a global leader in financial services with a focus on innovation.
  • Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
  • Other info: Be part of a collaborative team dedicated to advancing machine learning solutions.
  • Why this job: Make an impact in AI while collaborating with top experts in a dynamic environment.
  • Qualifications: PhD or MS in a quantitative field with strong machine learning and NLP experience.

The predicted salary is between 100000 - 130000 € per year.

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 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 them to tasks such as 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.

Required Qualifications, Capabilities, And Skills

  • PhD in a quantitative discipline such as Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, or an MS with significant 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.
  • 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.
  • 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 (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.

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 our people as 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.

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 are setting our businesses, clients, customers and employees up for success.

Applied AI ML Director - NLP / LLM and Graphs in London employer: hackajob

J.P. Morgan is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation within the Chief Data & Analytics Office. Employees benefit from extensive growth opportunities, access to cutting-edge technologies, and a commitment to diversity and inclusion, all while working in a prestigious global financial services environment. The Machine Learning Centre of Excellence provides a unique platform for professionals to engage with advanced machine learning techniques and contribute to impactful projects that drive the firm's commercial goals.

hackajob

Contact Detail:

hackajob Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied AI ML Director - NLP / LLM and Graphs in London

Tip Number 1

Network like a pro! Reach out to your connections in the industry, especially those at J.P. Morgan or similar firms. A friendly chat can sometimes lead to opportunities that aren’t even advertised.

Tip Number 2

Show off your skills! Prepare a portfolio or a presentation showcasing your past projects in NLP, LLM, and graph analytics. This will help you stand out during interviews and discussions.

Tip Number 3

Stay updated with the latest trends! Follow industry news and research papers related to machine learning and AI. Being knowledgeable about current advancements can give you an edge in conversations.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in being part of the team at J.P. Morgan.

We think you need these skills to ace Applied AI ML Director - NLP / LLM and Graphs in London

Natural Language Processing (NLP)
Large Language Models (LLM)
Graph Analytics
Machine Learning
Deep Learning
Agentic AI / Multi-Agent Systems
Experiment Design

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of Applied AI ML Director. Highlight your experience in NLP, LLM, and graph analytics, and don’t forget to showcase any hands-on projects that demonstrate your machine learning skills.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for machine learning and how your background aligns with J.P. Morgan's goals. Be sure to mention specific projects or experiences that relate to the job description.

Showcase Collaboration Skills:Since this role involves working with various teams, emphasise your collaborative experiences. Share examples of how you've successfully partnered with different departments to deploy solutions or drive initiatives.

Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves!

How to prepare for a job interview at hackajob

Know Your Stuff

Make sure you brush up on your knowledge of NLP, LLM, and graph analytics. Be ready to discuss specific projects you've worked on and the methodologies you used. This role is all about applying sophisticated machine learning methods, so having concrete examples will show you're the real deal.

Collaborate Like a Pro

Since this position involves working with various teams, be prepared to talk about your experience in collaborative environments. Share examples of how you've successfully partnered with business, technology, and compliance teams to deploy solutions. Highlight your ability to communicate complex concepts clearly to both technical and non-technical audiences.

Show Your Passion for Learning

This role values a strong desire to learn and innovate. Be ready to discuss any recent research, conferences you've attended, or new techniques you've experimented with in machine learning. Showing that you're proactive about staying current in the field will impress your interviewers.

Prepare for Technical Questions

Expect some deep dives into technical topics during your interview. Brush up on designing experiments, evaluating model performance, and big data challenges. Practising coding problems or discussing your approach to building agentic AI systems can also give you an edge.