Applied AI/ML [Multiple Positions Available]

JPMorgan Chase & Co.•Jersey City, NJ

8d•$165,000 - $195,000•Onsite

About The Position

This role involves executing artificial intelligence (AI) and machine learning (ML) software solutions. Responsibilities include design, development, and technical troubleshooting to build solutions and break down technical problems. The position requires creating secure production applications and maintaining AI algorithms that run synchronously with appropriate systems. Additionally, it involves producing ML and GenAI architecture components and design artifacts for applications, ensuring design constraints are met by software application development. The role also includes gathering, analyzing, and synthesizing data to develop models, integrations, visualizations, and reporting from large, diverse datasets for continuous improvement of software applications and systems. Identifying hidden problems and patterns in data to drive improvements to ML model pipelines, application hygiene, and system architecture is also a key duty. Finally, the position requires contributing to AI, ML, and software engineering communities of practice and events that explore new and emerging technologies.

Requirements

Master's degree in Computer Science, Computer Engineering, Information Technology, Data Science, or related field of study plus 3 years of experience in the job offered or as Applied AI/ML, Software Engineer, IT Consultant, or related occupation.
Alternatively, a Bachelor's degree in Computer Science, Computer Engineering, Information Technology, Data Science, or related field of study plus 5 years of experience in the job offered or as Applied AI/ML, Software Engineer, IT Consultant, or related occupation.
Three (3) years of experience with programming machine learning solutions using Python.
Three (3) years of experience developing software across front-end and back-end systems using cloud services such as AWS or Azure.
Three (3) years of experience developing and deploying AI/ML solutions using Kubernetes, Terraform, Docker, and AWS Cloud Services including EKS, ECS, SNS, SQS, and S3.
Three (3) years of experience implementing CI/CD pipelines using agile development frameworks.
Three (3) years of experience building scalable developer and business-facing financial applications using Java.
Three (3) years of experience building and optimizing regression and classification models using scikit-learn, XGBoost, and decision trees.
Three (3) years of experience developing personalized recommendation engines using collaborative and content-based filtering.
Three (3) years of experience performing feature engineering, label engineering, data cleaning, and exploratory data analysis for machine learning readiness.
Three (3) years of experience executing natural language processing using text classification, sentiment analysis, and entity extraction.
One (1) year of experience building developer and content generation platforms using front-end plugins, logging systems, alerting, and monitoring tools.
One (1) year of experience designing machine learning and neural search applications using microservice architecture, vector databases, and context engineering including semantic similarity, BM25, and OpenSearch.
One (1) year of experience applying AI and ML governance frameworks and compliance standards such as the FinOS AI Governance Framework in the financial industry.
One (1) year of experience building and fine-tuning transformer-based models using summarization and question answering.

Responsibilities

Execute artificial intelligence (AI) and machine learning (ML) software solutions.
Perform design, development, and technical troubleshooting to build solutions and break down technical problems.
Create secure production applications and maintain AI algorithms that run synchronously with appropriate systems.
Produce ML and GenAI architecture components and design artifacts for applications, ensuring that design constraints are met by software application development.
Gather analysis, and synthesize and develop models, integrations, visualizations, and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.
Identify hidden problems and patterns in data and use insights to drive improvements to ML model pipelines, application hygiene, and system architecture.
Contribute to Al, ML, and software engineering communities of practice and events that explore new and emerging technologies.