Wholesale Credit Risk Associate - Quantitative Research

JPMorgan Chase & Co.; Mumbai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

JPMorgan Chase & Co. in Mumbai seeks a Wholesale Credit Risk Associate - Quantitative Research / AI-ML Engineer to design and operationalize AI/ML solutions that drive business impact.

You will prepare and transform data, build scalable ETL pipelines in Python and Databricks, and contribute to model fine-tuning for domain tasks. Under senior guidance, you will deploy microservices on cloud platforms with Docker and Kubernetes, monitor performance, and communicate capabilities to both technical

Qualifications

• Master's degree in CS, Data Science or related field.
• 2+ years of experience in AI/ML or quantitative research.
• Proficient in Python and ML model development.
• Experience with cloud platforms and containerization.
• Experience building end-to-end data workflows and ETL pipelines.

Responsibilities

• Design, develop, and deploy AI/ML/LLM/Gen AI solutions to meet business objectives.
• Build scalable data pipelines for data, ensuring scalability, reliability, and efficiency.
• Fine-tune generative models for domain-specific use cases, with high-quality outputs.
• Evaluate model architectures and implement improvements to enhance performance.
• Implement monitoring to track AI/ML solution performance in real-time.
• Communicate AI capabilities and results to technical and non-technical audiences.
• Stay informed about latest AI/ML trends and leverage external APIs.

Skills

Python programming

Cloud platforms

Containerization

AI/ML model deployment

LangChain/LangGraph

Data pipelines

Databricks

Neo4j

Data modeling

Cross-functional collaboration

Education

Master's degree in Computer Science or Data Science

Tools

Databricks

AWS

Docker

Kubernetes

LangChain

LangGraph

Neo4j

ETL pipelines

Python

Job description

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.

As an Wholesale Credit Risk Associate - Quantitative Research / AI-ML Engineer you will support the design, development, and operationalization of AI/ML/LLM/Gen AI solutions that deliver measurable business impact. Working under the guidance of senior engineers, you will help prepare and transform data, build and maintain scalable ETL pipelines in Python and Databricks, and contribute to fine‑tuning and evaluating generative models for domain specific tasks such as summarization and text generation. You will assist in developing and deploying microservices on cloud platforms using Docker and Kubernetes, and support real‑time monitoring to ensure model and system performance.

Job Responsibilities:

• Design, develop, and deploy state-of-the-art AI/ML/LLM/Gen AI solutions to meet business objectives.
• Develop and maintain automated pipelines for data, ensuring scalability, reliability, and efficiency.
• Implement optimization strategies to fine‑tune generative models for domain specific use cases, ensuring high-quality outputs in summarization and text generation.
• Conduct thorough evaluations of generative models iterate on model architectures and implement improvements to enhance overall performance in AI/ML applications.
• Implement monitoring mechanisms to track AI/ML solutions performance in real‑time and ensure model reliability.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting‑edge techniques, and leverage external APIs for enhanced functionality.

Required Qualifications, Skills and Capabilities:

• Master’s with at least 2+ years’ experience in Computer Science, Data Science, Machine Learning, or a related field.
• Proficiency in Python for model development, experimentation, and integration with the LLM APIs.
• Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations, and fine‑tune models for optimal performance in AI/ML applications.
• Experience with cloud platforms (preferably AWS), containerization technologies (Docker and Kubernetes), and microservices design, implementation, and performance optimization.
• Proficient in building AI Agents (e.g., LangChain, LangGraph), integration of tools, and RAG-based solutions, Knowledge Graphs (e.g., neo4J).
• Experience developing end‑to‑end data workflows and ETL pipelines using Python and Databricks.
• Strong understanding of data modeling, normalization, and database design principles.
• Experience developing, debugging, and maintaining code in a large corporate environment using one or more modern programming languages and database querying languages.
• Ability to gather, analyze, and synthesize large, diverse data sets and to develop visualizations and reports in support of continuous improvement of applications and systems.
• Strong collaboration skills to work effectively with cross‑functional teams, communicate complex concepts, and contribute to interdisciplinary projects.