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- Tasks: Lead innovative AI projects using NLP, graphs, and machine learning to solve real-world challenges.
- Company: Join J.P. Morgan, a global leader in financial services, committed to diversity and inclusion.
- Benefits: Enjoy a collaborative environment, opportunities for learning, and access to cutting-edge technology.
- Why this job: Be part of a dynamic team driving impactful AI solutions in a supportive culture.
- Qualifications: PhD or MS in a quantitative field with strong machine learning and NLP experience required.
- Other info: Work with a multi-disciplinary team focused on advanced machine learning techniques.
The predicted salary is between 57600 - 84000 £ 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
- 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
- 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.
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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
Familiarise yourself with the latest advancements in NLP and graph analytics. Attend relevant conferences or webinars to network with industry professionals and gain insights that can set you apart during discussions.
✨Tip Number 2
Engage in online communities or forums focused on machine learning and AI. Sharing your knowledge and learning from others can help you build a strong professional network, which is crucial for collaboration in this role.
✨Tip Number 3
Showcase your hands-on experience with machine learning toolkits like TensorFlow and PyTorch by working on personal projects or contributing to open-source initiatives. This practical experience will demonstrate your capabilities effectively.
✨Tip Number 4
Prepare to discuss your approach to problem-solving and experimentation in machine learning. Be ready to share specific examples of how you've designed experiments and evaluated model performance in previous roles or projects.
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 highlights relevant experience in machine learning, NLP, and graph analytics. Use specific examples of projects you've worked on that align with the job description to demonstrate your expertise.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it relates to the role. Mention any significant achievements or research in the field, and explain why you are excited about the opportunity at JPMorgan Chase.
Showcase Your Technical Skills: Clearly outline your proficiency with machine learning toolkits like TensorFlow and PyTorch. Include any relevant certifications or courses that showcase your commitment to continuous learning in AI and ML.
Highlight Collaborative Experience: Since the role requires collaboration with various teams, provide examples of past experiences where you successfully worked in a team environment. Emphasise your ability to communicate complex technical concepts to both technical and non-technical audiences.
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with machine learning and deep learning toolkits like TensorFlow and PyTorch. Highlight specific projects where you've applied NLP or graph analytics, as this will demonstrate your capability to handle the technical demands of the role.
✨Demonstrate Collaborative Skills
Since the role requires collaboration with various teams, share examples of past experiences where you successfully worked with cross-functional teams. Emphasise your ability to communicate complex technical concepts to non-technical stakeholders.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical thinking and problem-solving skills. Be ready to discuss how you approach complex analytical problems and the methodologies you use to develop machine learning models that align with business goals.
✨Stay Updated on Industry Trends
Research recent advancements in machine learning, especially in NLP and reinforcement learning. Being knowledgeable about current trends and innovations will show your passion for the field and your commitment to continuous learning.
