Applied AI /ML Associate

JPMorgan Chase Bank; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

JPMorgan Chase Bank in Hyderabad seeks an experienced AI Practitioner to design and deploy AI-driven solutions for client onboarding and document operations. You will lead document intelligence models, LLM-based data extraction, and automation pipelines, delivering measurable improvements in accuracy and efficiency.

You will contribute as an individual contributor with potential to lead a team as the AI portfolio grows, applying banking domain knowledge to build production-grade solutions for

Qualifications

• 4+ years in AI/ML with at least 4 years in NLP, Document AI, or Generative AI.
• Strong ML/DL fundamentals (classification, clustering, entity extraction, semantic similarity).
• Hands-on with TensorFlow or PyTorch, scikit-learn, HuggingFace Transformers, and spaCy.
• Proven expertise in building document intelligence solutions (classification, OCR, key-value extraction, summarization).
• Proficiency in Python, SQL, Pandas; data ingestion and preprocessing pipelines.
• Experience deploying AI models to production with lifecycle management and monitoring.
• Experience with FastAPI or Flask, Docker, CI/CD, and API integration.
• Experience with LLM-driven workflows, prompt engineering, RAG, and LLM fine-tuning.
• Familiarity with OCR tools (Tesseract, Textract, Form Recognizer, or Google Document AI).
• Demonstrated ability to drive AI solution design and deployment independently.

Responsibilities

• Deliver production-grade AI solutions for document understanding and onboarding automation.
• Build and deploy LLM-powered extraction and summarization frameworks for unstructured documents.
• Achieve measurable improvements in accuracy, turnaround time (TAT), and operational efficiency.
• Develop reusable AI modules and APIs to enable rapid adoption across operations functions.
• Lead and expand a specialized AI team as solution scale and business demand increase.
• Design, implement, and optimize AI models and algorithms for diverse business applications.
• Collaborate with stakeholders to gather requirements and translate them into effective AI solutions.
• Analyze large datasets to extract actionable insights and support data-driven decisions.
• Ensure all AI initiatives comply with data privacy, governance, and ethical standards.
• Monitor and maintain model performance, retraining as needed to ensure reliability.
• Drive innovation by exploring emerging AI frameworks and technologies for continuous improvement.

Skills

NLP

Document AI

Generative AI

Machine Learning

Deep Learning

Python

SQL

Pandas

TensorFlow

PyTorch

HuggingFace Transformers

spaCy

LLM workflows

Prompt engineering

RAG

LLM fine-tuning

Education

Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field

Tools

FastAPI

Flask

Docker

CI/CD

API integration

Tesseract

Textract

Form Recognizer

Job description

Are you ready to shape the future of banking with cutting-edge AI solutions Join our dynamic team to transform client onboarding and document operations, partnering with business leaders to deliver measurable results in a fast-paced, collaborative environment.

Job Summary

As an AI Practitioner within the client onboarding and documentation organization, you will:

• Design and implement AI-driven solutions to streamline onboarding and document-intensive banking operations.
• Lead the development and deployment of document intelligence models, LLM-based data extraction frameworks, and automation pipelines to improve efficiency and accuracy.
• Serve as an individual contributor, deeply involved in solution design, model development, and deployment.
• Potentially transition into a team leadership role as the AI portfolio grows and solutions scale across functions.
• Apply advanced AI expertise and banking domain knowledge to deliver impactful, production-grade solutions for onboarding and KYC processes.

Job Responsibilities

• Deliver production-grade AI solutions for document understanding and onboarding automation.
• Build and deploy LLM-powered extraction and summarization frameworks for unstructured documents.
• Achieve measurable improvements in accuracy, turnaround time (TAT), and operational efficiency.
• Develop reusable AI modules and APIs to enable rapid adoption across operations functions.
• Lead and expand a specialized AI team as solution scale and business demand increase.
• Design, implement, and optimize AI models and algorithms for diverse business applications.
• Collaborate with stakeholders to gather requirements and translate them into effective AI solutions.
• Analyze large datasets to extract actionable insights and support data-driven decisions.
• Ensure all AI initiatives comply with data privacy, governance, and ethical standards.
• Monitor and maintain model performance, retraining as needed to ensure reliability.
• Drive innovation by exploring emerging AI frameworks and technologies for continuous improvement.

Required Qualifications, Capabilities, and Skills

• Atleast4 years of experience in AI/ML, with at least 4 years in NLP, Document AI, or Generative AI.
• Strong foundation in machine learning and deep learning algorithms (classification, clustering, entity extraction, semantic similarity).
• Hands-on experience with TensorFlow or PyTorch, scikit-learn, HuggingFace Transformers, and spaCy.
• Proven expertise in building document intelligence solutions (classification, OCR, key-value extraction, summarization).
• Proficiency in Python, SQL, Pandas, and experience with data ingestion and preprocessing pipelines.
• Experience deploying AI models to production, including lifecycle management and monitoring.
• Skilled in FastAPI or Flask, Docker, CI/CD, and API integration.
• Strong experience with LLM-driven workflows, prompt engineering, RAG, and LLM fine-tuning.
• Familiarity with OCR tools (Tesseract, Amazon Textract, Azure Form Recognizer, or Google Document AI).
• Demonstrated ability to drive AI solution design and deployment independently.
• Bachelor s or Master s degree in Computer Science, AI, Data Science, or related field.

Preferred Qualifications, Capabilities, and Skills

• Experience in banking client onboarding, KYC/AML, and document verification processes.
• Familiarity with corporate onboarding documentation and regulatory compliance in BFSI or regulated domains.
• Experience with multimodal document models (LayoutLMv3, Donut, DocFormer) and advanced NER/entity linking.
• Integration experience with OpenAI, Anthropic, Cohere, or open-source LLMs (LLaMA, Mistral).
• Knowledge of data privacy, governance, and AI explainability frameworks in financial services.
• Track record of cross-functional collaboration with operations, data engineering, and low-code teams.
• Ph.D. or advanced specialization in AI or related field.