Applied AI/ML Lead

Testing Site - JPMC; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

JPMorgan Chase in Bengaluru seeks a Data Scientist Lead to drive prompt-based LLM initiatives within Asset and Wealth Management. You will design, deploy and optimize NLP models, build data pipelines, and collaborate with diverse teams to deliver scalable, secure AI solutions for financial services.

Ideal candidates will have 5+ years of experience, strong Python development skills (PyTorch/TensorFlow), cloud deployment know-how (AWS/Azure), and a proven ability to communicate complex results to

Qualifications

• Formal training or certification on software engineering concepts.
• 5+ years applied experience in relevant domain.
• Experience with prompt design and chatbot applications.
• Strong programming skills in Python with PyTorch or TensorFlow.
• Experience building data pipelines for structured and unstructured data.
• Develop APIs and integrate NLP/LLM models into software.
• Hands-on cloud experience (AWS or Azure) for AI/ML deployment.
• Clear communication with technical and leadership stakeholders.
• Knowledge of deployment processes and version control (Git).
• Familiarity with LLM orchestration and agentic AI libraries.
• MLOps experience for production ML model integration.

Responsibilities

• Design, deploy and manage prompt-based models on LLMs for NLP tasks in finance.
• Research prompt engineering techniques to improve performance and orchestration.
• Collaborate with cross-functional teams to meet business needs.
• Communicate effectively with technical and non-technical stakeholders.
• Build and maintain data pipelines and workflows on cloud platforms.
• Develop tools/frameworks for prompt-based model training and evaluation.
• Analyze data to evaluate model performance and identify improvements.

Skills

Software engineering concepts

Experience >=5 years

Prompt design

APIs

NLP/LLM integration

Communication skills

LLM orchestration

Agentic AI libraries

MLOps

Problem solving

Tools

Python

PyTorch

TensorFlow

AWS

Azure

Spark

Java

Git

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Data Scientist Lead at JPMorgan Chase within the Asset and Wealth Management, youare an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Design, deploy and manage prompt-based models on LLMs for various NLP tasks in the financial services domain
• Conduct research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
• Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization
• Communicate effectively with both technical and non-technical stakeholders
• Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
• Develop and maintain tools and framework for prompt-based model training, evaluation and optimization
• Analyze and interpret data to evaluate model performance to identify areas of improvement

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Experience with prompt design and implementation or chatbot application
• Strong programming skills in Python with experience in PyTorch or TensorFlow
• Experience building data pipelines for both structured and unstructured data processing.
• Experience in developing APIs and integrating NLP or LLM models into software applications
• Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
• Excellent problem-solving and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner
• Basic knowledge of deployment processes, including experience with GIT and version control systems
• Familiarity with LLM orchestration and agentic AI libraries
• Hands on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environment

Preferred qualifications, capabilities, and skills

• Familiarity with model fine-tuning techniques such as DPO and RLHF.
• Knowledge of Java, Spark
• Knowledge of financial products and services including trading, investment and risk management