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JPMorganChase provides banking, financing, asset management and payment processing services to individuals, businesses, institutions and governments.

Job details

The full description published by JPMorganChase.

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Description de l’offre

J.P. Morgan is seeking a Software Engineer with expertise in AWS and Python, and a passion for Machine Learning, to help engineer and deploy innovative ML solutions into production. You will join the Applied AI/ML Software Engineering team, collaborating with technology teams across the firm, contributing to both new and ongoing projects. As a Software Engineer III at JPMorganChase within the CIB Security Services Technology Applied AIML team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products 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. In this role, you will work alongside Data Scientists to build cloud-based frameworks for hosting machine learning models, providing software engineering expertise throughout the model development lifecycle. You will leverage both internal and external cloud platforms, utilizing proprietary and open-source tools to ensure models meet SDLC standards, are production-ready, and can be deployed efficiently.

The position requires close interaction with platform developers, engineering communities, and the integration of existing and new technologies.

Job Responsibilities

Develop and maintain high-quality, secure applications using Python and AWS

  • Create architecture and design deliverables
  • Integrate AIML solutions into complex, domain-specific operations processing systems
  • Participate in code reviews, design discussions, and agile planning sessions
  • Collaborate with SRE and production monitoring teams to ensure system reliability and performance
  • Contribute to software engineering communities of practice and technology events
  • Embrace continuous learning, creative problem-solving, and a can-do attitude

Required Qualifications

, Capabilities, and Skills

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent formal training/certification
  • Proven hands-on experience in Python application development
  • Proven hands-on experience developing, debugging and maintaining production applications
  • Solid understanding of software development best practices, including version control, testing, and CI/CD
  • Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
  • Familiarity with Machine Learning Operations (MLOps)
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Preferred

Qualifications

, Capabilities, and Skills

  • Experience with Cloud services, Infrastructure as Code (IaC) and containerized application development
  • Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock
  • Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps)
  • Experience working on AIML systems and/or prior experience collaborating with data scientists

Requirements

  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field
  • Python application development
  • Production applications
  • Software development best practices
  • Problem-solving
  • Communication
  • Collaboration

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