Machine Learning Software Engineer-Senior Associate
Company: JPMorgan Chase & Co.
Location: Houston
Posted on: April 3, 2026
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Job Description:
Description J.P. Morgan is a global leader in financial
services, providing strategic advice and products to the world’s
most prominent corporations, governments, wealthy individuals and
institutional investors. Our first-class business in a first-class
way approach to serving clients drives everything we do. We strive
to build trusted, long-term partnerships to help our clients
achieve their business objectives. As a Machine Learning Software
Engineer within JPMorgan, you will be a vital member of an agile
team, tasked with designing and delivering secure, stable, and
scalable market-leading technology products. Your role involves
implementing critical technology solutions across a variety of
technical areas within different business functions, all in support
of the firm's business objectives. Job responsibilities Work with
product managers, data scientists, ML engineers, and other
stakeholders to understand requirements. Design, develop, and
deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business
objectives. Develop and maintain automated pipelines for model
deployment, ensuring scalability, reliability, and efficiency.
Implement optimization strategies to fine-tune generative models
for specific NLP use cases, ensuring high-quality outputs in
summarization and text generation. Conduct thorough evaluations of
generative models (e.g., GPT-4), iterate on model architectures,
and implement improvements to enhance overall performance in NLP
applications. Implement monitoring mechanisms to track model
performance in real-time and ensure model reliability. Communicate
AI/ML/LLM/GenAI capabilities and results to both technical and
non-technical audiences. Required qualifications, capabilities, and
skills Bachelor's or Master's degree in Computer Science,
Engineering, or a related field Minimum 3 years of demonstrated
experience in applied AI/ML engineering, with a track record of
developing and deploying business critical machine learning models
in production. Proficiency in programming languages like Python for
model development, experimentation, and integration with OpenAI
API. Experience with machine learning frameworks, libraries, and
APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
Experience with cloud computing platforms (e.g., AWS, Azure, or
Google Cloud Platform), containerization technologies (e.g., Docker
and Kubernetes), and microservices design, implementation, and
performance optimization. Solid understanding of fundamentals of
statistics, machine learning (e.g., classification, regression,
time series, deep learning, reinforcement learning), and generative
model architectures, particularly GANs, VAEs. Ability to identify
and address AI/ML/LLM/GenAI challenges, implement optimizations and
fine-tune models for optimal performance in NLP applications.
Strong collaboration skills to work effectively with
cross-functional teams, communicate complex concepts, and
contribute to interdisciplinary projects. Preferred qualifications,
capabilities, and skills Familiarity with the financial services
industries. Expertise in designing and implementing pipelines using
Retrieval-Augmented Generation (RAG). Hands-on knowledge of
Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting
strategies. A portfolio showcasing successful applications of
generative models in NLP projects, including examples of utilizing
OpenAI APIs for prompt engineering.
Keywords: JPMorgan Chase & Co., Beaumont , Machine Learning Software Engineer-Senior Associate, IT / Software / Systems , Houston, Texas
