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Applied AI/ML Engineer

JPMorgan Chase

Bengaluru

4-6 years

Today

$34.9K–49.4K/yr

Full time

Onsite

Skills Required

LLM

RAG

Prompt Engineering

LangChain

LangGraph

Google ADK

Machine Learning

NLP

Deep Learning

Knowledge Graphs

Python

FastAPI

SQL

AWS

SageMaker

Description

Applied AI/ML role focused on building agent-driven systems and trusted market-leading technology products at scale. The position emphasizes secure, stable, scalable AI/ML solutions for business problems.

Company: JPMorgan Chase

Role: Applied AI/ML Engineer

Location: Bengaluru, Karnataka, India

Experience

- 4+ years of working experience as a hands-on ML Engineer, Data Engineer, or Data Scientist
- At least 6 years of industry experience
- Experience managing stakeholders from diverse backgrounds

Qualification

- Advanced Degree in Computer Science, Data Science, or equivalent discipline

Responsibilities

- Design and deliver trusted market-leading technology products using AI/ML technologies
- Carry out critical technology solutions across multiple technical areas in support of business objectives
- Incorporate LLM models in business solutions
- Build and enhance the AI processing pipeline for higher throughput and accuracy
- Customize solutions for specific use cases using Langchain, few shot learning, Chain of thought, and prompt engineering techniques
- Develop production-grade agentic workflows with modern orchestration frameworks
- Focus on evaluation, observability, resilience, and maintainability
- Explore LLM models and evaluate model performance and accuracy
- Implement RAG methods to improve retrieval and answer generation from large datasets
- Develop end-to-end ML pipelines to transform applications and business processes into AI systems
- Collaborate with cross-functional teams to define requirements and deliver high-quality solutions




- Develop large-scale data modeling experiments and evaluate against strong baselines
- Extract key statistical insights and cause-and-effect relations
- Tune and optimize LLMs for specific use cases and improve response accuracy and relevance

Additional Responsibilities

- Work in a secure, stable, and scalable way
- Build systems that reach JPMorgan scale

Nice To Have

- Experience as a Senior Data Scientist driving projects end to end
- Experience in LLM and building RAG pipeline
- Experience in large scale Machine Learning system design
- Experience working with end-to-end pipelines consisting of Cloud services
- Experience with AWS ML ecosystem such as Sagemaker
- Experience with TensorFlow or PyTorch over GPU
- Experience with BERT and SBERT

More Skills analytics, AWS suite, machine learning techniques, advanced analytics, regression, classification, clustering, causal inference, mathematical optimization, few shot learning, Chain of thought, agentic workflows, evaluation, observability, resilience, maintainability, Retrieval-Augmented Generation (RAG), ML pipelines, large-scale data modeling, TensorFlow, PyTorch, GPU, BERT, SBERT, AWS ML ecosystem

Prepare for this role

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