Applied Artificial Intelligence and Machine Learning Engineer

JP Morgan Services India Pvt Ltd; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

JP Morgan Services India Pvt Ltd in Bengaluru seeks an Applied AI/ML Engineer to shape intelligent products by building agent-driven systems at scale. You will design and deliver trusted AI/ML tech in a secure, scalable fashion.

You will leverage ML, NLP, deep learning, knowledge graphs, LLMs and large datasets to build JPMorgan-scale systems. Collaboration with cross-functional teams is essential for success.

Qualifications

• Advanced degree in CS/DS or equivalent.
• 4+ years hands-on ML/DS engineering experience.
• Strong stakeholder management and communication.

Responsibilities

• Incorporate LLM models in business solutions.
• Build AI processing pipelines for throughput and accuracy.
• Develop production-grade agentic workflows and RAG pipelines.
• Collaborate with data scientists and engineers to deliver solutions.
• Evaluate model performance and improve accuracy.

Skills

Python

FastAPI

Deep Learning

NLP

Distributed ML

SQL

AWS

Education

Advanced Degree in Computer Science or Data Science

Tools

Langchain

LangGraph

Google ADK

TensorFlow

PyTorch

REST APIs

Job description

Applied AI/ML Engineer

Shape the future of intelligent products by building agent-driven systems that solve meaningful business problems at scale As an Applied AI ML Associate Senior at JPMorgan Chase, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products using AI/ML technologies in a secure, stable, and scalable way.

You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

You will need to leverage your strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs, LLM, and experience in working with massive amounts of data to build systems that reach JP Morgan scale.

Job responsibilities

• Incorporate LLM models in business solutions.
• Build and enhance the AI processing pipeline to achieve higher throughput and accuracy by customizing for specific use cases by using tools like Langchain, few shot learning, Chain of thought and other prompt engineering techniques.
• Develop production-grade agentic workflows using modern orchestration frameworks (e.g. LangGraph , Google ADK and other agent frameworks), with strong focus on evaluation , observability, resilience, and maintainability.
• Explore LLM models and evaluate model performance and accuracy.
• Improve the accuracy of the models by customizing for specific use cases.
• Implement Retrieval-Augmented Generation (RAG) methods to enhance the LLM's ability to retrieve and generate accurate answers from large datasets.
• Develop end-to-end ML pipelines necessary to transform existing applications and business processes into true AI systems.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define requirements and deliver high-quality solutions.
• You will collaborate to develop large-scale data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
• Utilize Prompt Engineering techniques to fine-tune and optimize LLMs for specific use cases and improve response accuracy and relevance.

Required qualifications, capabilities, and skills

• Advanced Degree in field of Computer Science, Data Science or equivalent discipline
• 4+ years of working experience as a hands-on ML Engineer/Data Engineer/Data Scientist, with at least 6 years of industry experience
• Strong communication skills along with significant experience of managing stakeholder of diverse background
• Hands on expertise with Python, Fast API and DL
• Experience in designing and building highly scalable distributed ML models in production.
• Experience with analytics (ex: SQL, Python, AWS suite)
• Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, causal inference, mathematical optimization)

Preferred qualifications, capabilities, and skills

• Experience as a Senior Data Scientist , in driving projects end to end is preferred
• Experience in LLM, building RAG pipeline is preferred
• Experience in large scale Machine Learning system design is preferred
• Experience working with end-to-end pipelines consisting of Cloud services is preferred
• Experience with AWS ML ecosystem (i.e. Sagemaker, etc.) is good to have.
• Frameworks like TensorFlow/PyTorch over GPU is preferred, BERT, SBERT,etc

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands.

Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success.

We are an equal opportunity employer and place a high value on diversity and inclusion at our company.

We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.

We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.

Visit FAQs for more information about requesting an accommodation.

Experience Level Senior Level