At a Glance
- Tasks: Revolutionise banking with AI/ML solutions and enhance client services.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse culture, and opportunities for growth.
- Other info: Collaborative environment that values diversity and innovation.
- Why this job: Shape the future of banking and make a real impact.
- Qualifications: Advanced degree or significant experience in AI/ML and Python programming.
The predicted salary is between 70000 - 90000 £ per year.
This is a rare opportunity to help shape the future of our Private Bank. With the sponsorship from the CEO and the heads of the business, our goal is to create an Agentic Private Bank - reimagining the entire process from start to finish, rethinking the operating model including organizational structures and developing AI agents equipped with the latest tools and technologies to fundamentally reshape how we perform this business. Join our dynamic team of innovators and technologists as a Senior Applied AI/ML Associate, where your mission will be to revolutionise how the Bank services and advises clients, deepen client engagements, and drive process transformation. You will analyse existing processes and vast amounts of data to design autonomous AI agents. We seek individuals passionate about leveraging advanced data analysis, statistical modelling, and AI/ML techniques to solve complex business challenges through high-quality, cloud-centric software delivery. Our culture thrives on experimentation, continuous improvement, and learning. You will work in a collaborative, trusting, and intellectually stimulating environment - one that values diversity of thought and fosters creative solutions that serve the best interests of our global clientele.
Job Responsibilities
- Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
- Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation.
- Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilised across investment functions, client services, and operational processes.
- Collect and curate datasets for model training and evaluation.
- Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results.
- Monitor and improve model performance through feedback and active learning.
- Collaborate with technology teams to deploy and scale the developed models in production.
- Deliver written, visual, and oral presentation of modelling results to business and technical stakeholders.
- Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement.
Required qualifications, capabilities, and skills
- Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry.
- Experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, summarisation, personalisation, classification or forecasting.
- Advanced Python programming skills with experience writing production quality code.
- Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, gradient descent etc.
- Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace.
- Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation.
- Familiarity with latest developments in deep learning frameworks.
- Ability to communicate complex concepts and results to both technical and business audiences.
Preferred qualifications, capabilities, and skills
- Prior experience of developing solutions for Financial domain.
- Exposure to distributed model training, and deployment.
- Familiarity with techniques for model explainability and self-validation.
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 recognise 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, colour, 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.
About The Team
J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realise their goals.
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We think you need these skills to ace AI/ML Lead- Agentic AI
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