Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead innovative AI projects using NLP, LLM, and graph analytics to solve real-world problems.
- Company: Join JPMorgan Chase's Chief Data & Analytics Office, a leader in data-driven solutions.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make an impact with cutting-edge machine learning technologies in a collaborative environment.
- Qualifications: PhD or MS in a quantitative field with strong machine learning expertise.
- Other info: Be part of a dynamic team focused on pioneering machine learning solutions.
The predicted salary is between 72000 - 108000 £ 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 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
- 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 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.
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.
- 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.
- 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.
- 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.
Applied AI ML Director - NLP / LLM and Graphs employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI ML Director - NLP / LLM and Graphs
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or conferences, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to NLP and graphs. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies alike.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Applied AI ML Director - NLP / LLM and Graphs
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the job description. Highlight your expertise in NLP, LLM, and graph analytics, as well as any hands-on experience with machine learning tools like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about machine learning and how your background makes you a great fit for the role. Share specific examples of projects or research that demonstrate your analytical thinking and collaborative spirit.
Showcase Your Communication Skills: Since effective communication is key, ensure your application materials clearly convey complex technical concepts in an understandable way. This will show us that you can bridge the gap between technical and business audiences.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity within the Chief Data & Analytics Office.
How to prepare for a job interview at Jpmorgan Chase & Co.
✨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 machine learning methods you've applied. This shows you're not just familiar with the concepts but have practical experience too.
✨Show Your Collaborative Spirit
Since this role involves working with various teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your ability to communicate complex technical concepts to non-technical audiences, as this will be crucial in a cross-functional environment.
✨Demonstrate Your Passion for Learning
Express your enthusiasm for continuous learning and innovation in machine learning. Mention any recent conferences you've attended or new techniques you've experimented with. This will show that you're proactive and genuinely interested in advancing your skills.
✨Prepare for Technical Questions
Expect to face technical questions related to machine learning frameworks like TensorFlow or PyTorch. Brush up on designing experiments and evaluating model performance metrics. Being able to articulate your thought process clearly will impress the interviewers.
