Applied AI ML Associate

JPMorganChase • Jersey City, NJ

3d

About The Position

Join JPMorganChase’s Wholesale Payments Operations team to turn advanced machine learning and modern software engineering into solutions that improve global payments operations. The role partners with business and technology stakeholders to deliver measurable outcomes, including faster decisioning, improved risk detection, and smarter workflows, while building reliable, production-ready services.

As an Applied AI/Machine Learning Engineer, you will build, deploy, and continuously improve AI-enabled products for complex, high-impact business problems. You will translate ambiguous opportunities into technical approaches, develop models and services for real production conditions, and contribute to responsible, scalable adoption of modern AI in a collaborative environment that values ownership, learning, and outcomes.

Requirements

• Formal training or certification in applied artificial intelligence and machine learning concepts, with 2+ years of applied experience.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Hands-on Python experience building production-grade software, including services, APIs, testing, and refactoring.
• Experience deploying services to cloud infrastructure and supporting production requirements such as reliability, observability, and latency.
• Ability to apply machine learning to real-world text and document use cases and evaluate model quality using clear metrics.
• Strong software engineering fundamentals, including object-oriented design and concurrency concepts.
• Experience taking work from problem definition through deployment and iteration, while communicating tradeoffs and progress to partners.
• Experience using AI coding assistants responsibly to improve delivery speed while maintaining code quality, security-mindedness, and test coverage.
• Strong communication skills and a collaborative working style.

Nice To Haves

• Experience with managed machine learning platforms, such as Amazon SageMaker or equivalent, for training and deployment workflows.
• Experience building and operating large language model solutions, including structured evaluation approaches and guardrails.
• Experience productionizing natural language processing and/or document understanding solutions at scale.
• Experience designing AI-enabled automation workflows with measurable quality and ongoing production monitoring.
• Familiarity with prompt design and iterative improvement practices that make AI behavior reviewable and reproducible.

Responsibilities

• Frame AI problems, define success metrics, and deliver production releases that produce measurable operational impact.
• Partner with operations, product, and engineering stakeholders to design workflows that augment decision-making and reduce manual effort.
• Build and deploy cloud-based AI services with reliability, monitoring, and operational readiness.
• Develop and maintain data and evaluation pipelines for repeatable training, testing, and continuous production improvement.
• Apply machine learning to text and document use cases, including natural language processing, classification, document understanding, and optical character recognition.
• Design AI-enabled automation with safeguards, defining interfaces, controlling behavior, and measuring quality, latency, and cost tradeoffs.
• Improve codebases through refactoring, testing, documentation, and engineering best practices.
• Diagnose model and service performance issues, identify root causes, and implement improvements based on evidence and feedback.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level