Applied AI /ML Associate

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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.