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- Tasks: Lead innovative AI projects using NLP and machine learning to solve real-world challenges.
- Company: Join JPMorgan Chase, a global leader in financial services with a commitment to diversity and inclusion.
- Benefits: Enjoy a collaborative work environment, opportunities for continuous learning, and access to cutting-edge technology.
- Why this job: Be part of a dynamic team driving impactful AI solutions that enhance productivity and decision-making.
- Qualifications: PhD or MS in a quantitative field with strong experience in machine learning and deep learning.
- Other info: Engage in knowledge sharing and attend industry-leading conferences to stay ahead in the field.
The predicted salary is between 43200 - 72000 £ per year.
Applied AI ML Director – NLP / LLM and Graphs
Join to apply for the Applied AI ML Director – NLP / LLM and Graphs role at JPMorgan Chase
Job Description
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 them 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 industry or research experience in the field
- Solid background in NLP, LLM, and graph analytics with 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 evaluate model performance metrics aligned with business goals
- Experience with big data and scalable model training, along with effective communication skills to convey technical concepts to technical and business audiences
- Scientific thinking, independent and collaborative working skills, curiosity, hardworking, and detail-oriented with motivation for complex analytical problems
Preferred Qualifications, Capabilities, And Skills
- Strong background in Mathematics and Statistics, familiarity with financial services, and experience with continuous integration and unit testing
- Knowledge in search/ranking, Reinforcement Learning, or Meta Learning
- Experience with A/B testing, data-driven product development, cloud-native deployment, and production-quality coding
- Published research in Machine Learning, Deep Learning, or Reinforcement Learning at major conferences or journals
About MLCOE
The Machine Learning Center of Excellence (MLCOE) partners across the firm to create and share ML solutions for challenging business problems. You will work with a multidisciplinary team focused on cutting-edge techniques in Deep Learning and Reinforcement Learning. For more information, visit http://www.jpmorgan.com/mlcoe.
About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to prominent clients worldwide. We value diversity and inclusion, and are committed to equal opportunity employment, making reasonable accommodations for applicants and employees.
About The Team
Our professionals cover a wide range of corporate functions, ensuring the success of our business, clients, and employees.
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Applied AI ML Director - NLP / LLM and Graphs employer: JPMorganChase
Contact Detail:
JPMorganChase 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 with professionals in the AI and machine learning field, especially those who work at JPMorgan Chase or similar companies. Attend industry conferences and meetups to connect with potential colleagues and learn about the latest trends in NLP and graph analytics.
✨Tip Number 2
Showcase your hands-on experience with machine learning tools like TensorFlow and PyTorch by contributing to open-source projects or creating your own projects. This practical experience can set you apart and demonstrate your ability to apply theoretical knowledge in real-world scenarios.
✨Tip Number 3
Engage in online forums and communities focused on NLP and machine learning. Sharing your insights and asking questions can help you build a reputation in the field and may even lead to job referrals or recommendations.
✨Tip Number 4
Prepare for interviews by familiarising yourself with common machine learning case studies and problems related to NLP and graph analytics. Practising how to articulate your thought process and solutions will help you impress interviewers with your analytical thinking and problem-solving skills.
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 your experience in machine learning, NLP, and graph analytics. Use specific examples of projects you've worked on that demonstrate your expertise in these areas.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with the goals of JPMorgan Chase. Mention any relevant research or projects that showcase your skills and how you can contribute to their team.
Showcase Your Technical Skills: Clearly outline your proficiency with machine learning toolkits like TensorFlow and PyTorch. Include any relevant certifications or courses that support your qualifications for the role.
Highlight Collaborative Experience: Since the role requires collaboration with various teams, provide examples of past experiences where you successfully worked with cross-functional teams to deploy solutions. This will demonstrate your ability to thrive in a collaborative environment.
How to prepare for a job interview at JPMorganChase
✨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 tackle the role's responsibilities.
✨Demonstrate Collaborative Skills
Since the role requires working with various teams, share examples of past collaborations. Discuss how you effectively communicated technical concepts to non-technical stakeholders, showcasing your ability to bridge the gap between technology and business.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your analytical thinking and problem-solving skills. Practice articulating your thought process when designing experiments or evaluating model performance metrics, as this will reflect your scientific approach.
✨Express Your Passion for Learning
Convey your enthusiasm for continuous learning and innovation in machine learning. Mention any recent conferences you've attended or new methods you've explored, as this aligns with the company's focus on research and development in AI technologies.
