Applied AI ML Associate Senior at JPMC Candidate Experience page

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

11 Jun, 26

Salary

0.0

Posted On

13 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI ML, LLM, Agentic Applications, Data Architecture, ML Platform, GenAI Platform, Distributed ML Platform, Large Language Models, Python, Java, NLP, Deep Learning, PyTorch, TensorFlow, Prompt Engineering, RAG

Industry

Financial Services

Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As an Applied AI ML Associate Senior within JPMorgan Chase Digital Technology, you will lead the development and innovation of agentic applications using LLM technologies. You will work closely with a talented team to design scalable, resilient applications with strong observability, contributing to JP Morgan Chase's mission of delivering exceptional self-service solutions. Your role will be pivotal in driving innovation and enhancing the user experience, making a difference in the lives of our clients and the wider community. Job Responsibilities * Develop solutions related to data architecture, ML Platform as well as GenAI platform architecture, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures * Serve as a subject matter expert on a wide range of ML techniques and optimizations. * Provide in-depth knowledge of distributed ML platform deployment including training and serving. * Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques. * Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. * Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team. * Own end to end code development in python/Java for both proof of concept/experimentation and production-ready solutions. * Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks and collaborate with product and engineering teams to deliver tailored, science and technology-driven solutions. * Drives decisions that influence the product design, application functionality, and technical operations and processes. Required Qualifications, Capabilities, and Skills * Formal training or certification on AI ML concepts and 3+ years applied experience * Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs) * Hands-on experience with machine learning and deep learning methods. * Good understanding in deep learning frameworks such as PyTorch or TensorFlow. * Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search). * Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. * Practical cloud native experience such as AWS Preferred Qualifications, Capabilities, and Skills * Experience with Ray, MLFlow, and/or other distributed training frameworks. * In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. * Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker. * Exposure to agentic frameworks such as Langchain, Langgraph, RASA, Parlant, Decagon. 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 our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

Responsibilities

The role involves leading the development and innovation of agentic applications using LLM technologies, focusing on designing scalable and resilient applications with strong observability. Responsibilities include developing solutions for data architecture, ML/GenAI platform architecture, and serving as a subject matter expert on ML techniques and distributed ML platform deployment.